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Nazarpour S, Shokati Poursani A, Mousavi M, Ramezani Tehrani F, Behboudi-Gandevani S. Investigation of the relationship between air pollution and gestational diabetes. J OBSTET GYNAECOL 2024; 44:2362962. [PMID: 38853776 DOI: 10.1080/01443615.2024.2362962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 05/27/2024] [Indexed: 06/11/2024]
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) can have negative effects on both the pregnancy and perinatal outcomes, as well as the long-term health of the mother and the child. It has been suggested that exposure to air pollution may increase the risk of developing GDM. This study investigated the relationship between exposure to air pollutants with gestational diabetes. METHODS The present study is a retrospective cohort study. We used data from a randomised community trial conducted between September 2016 and January 2019 in Iran. During this period, data on air pollutant levels of five cities investigated in the original study, including 6090 pregnant women, were available. Concentrations of ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 (PM2.5) or <10 μm (PM10) were obtained from air pollution monitoring stations. Exposure to air pollutants during the three months preceding pregnancy and the first, second and third trimesters of pregnancy for each participant was estimated. The odds ratio was calculated based on logistic regression in three adjusted models considering different confounders. Only results that had a p < .05 were considered statistically significant. RESULTS None of the logistic regression models showed any statistically significant relationship between the exposure to any of the pollutants and GDM at different time points (before pregnancy, in the first, second and third trimesters of pregnancy and 12 months in total) (p > .05). Also, none of the adjusted logistic regression models showed any significant association between PM10 exposure and GDM risk at all different time points after adjusting for various confounders (p > .05). CONCLUSIONS This study found no association between GDM risk and exposure to various air pollutants before and during the different trimesters of pregnancy. This result should be interpreted cautiously due to the lack of considering all of the potential confounders.
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Affiliation(s)
- Sima Nazarpour
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Department of Midwifery, Varamin-Pishva Branch, Islamic Azad University, Tehran, Iran
| | - Afshin Shokati Poursani
- Department of Chemical Engineering - Health, Safety & Environment, Najafabad Branch, Islamic Azad University, Najafabad, Iran
| | - Maryam Mousavi
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fahimeh Ramezani Tehrani
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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LaPointe S, Nie J, Stevens DR, Gleason JL, Ha S, Seeni I, Grantz KL, Mendola P. Exposure to acute ambient temperature extremes and neonatal intensive care unit admissions: A case-crossover study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 953:176149. [PMID: 39260482 DOI: 10.1016/j.scitotenv.2024.176149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 08/13/2024] [Accepted: 09/07/2024] [Indexed: 09/13/2024]
Abstract
BACKGROUND Extreme in utero temperatures have been associated with adverse birth outcomes, including preterm birth and low birthweight. However, there is limited evidence on associations with neonatal intensive care unit (NICU) admissions, which reflect a range of poor neonatal health outcomes. METHODS This case-crossover study assesses the associations between ambient temperature changes during the week of delivery and risk of NICU admission. Data from the Consortium on Safe Labor (2002-2008) were linked to ambient temperature at hospital referral regions. Adjusted hazard ratios (HR) and 95 % confidence intervals (CI) estimated NICU admission risk with a 1 °C increase on each day of the week of delivery and of the average weekly temperature, adjusted for particulate matter ≤2.5 μm (PM2.5) and relative humidity. We also estimated associations with 1 °C increases and 1 °C decreases in temperatures during weeks of site-specific extreme heat (>90th and 95th percentiles) and cold (<5th and 10th percentiles), respectively. RESULTS There were 27,188 NICU admissions with median (25th, 75th) temperature of 16.4 °C (5.8, 23.0) during the week before delivery. A 1 °C increase in temperature during the week of delivery was not associated with risk of NICU admission. However, analyses of extreme temperatures found that a 1 °C decrease in weekly average temperatures below the 10th and 5th percentiles was associated with 30 % (aHR = 1.30, 95 % CI 1.28, 1.31) and 47 % (aHR = 1.47, 95 % CI 1.45, 1.50) increased risk of NICU admissions, while a 1 °C increase in weekly average temperatures above the 90th and 95th percentiles was associated with more than two- (aHR = 2.29, 95 % CI 2.17, 2.42) and four-fold (aHR = 4.30, 95 % CI 3.68, 5.03) higher risk of NICU admission, respectively. CONCLUSIONS Our study found temperature extremes in the week before delivery increased NICU admission risk, particularly during extreme heat, which may translate to more adverse neonatal outcomes as extreme temperatures persist.
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Affiliation(s)
- Sarah LaPointe
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY, USA
| | - Jing Nie
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY, USA
| | - Danielle R Stevens
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Jessica L Gleason
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - Sandie Ha
- Department of Public Health, Health Science Research Institute, University of California Merced, Merced, CA, USA
| | - Indulaxmi Seeni
- Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Katherine L Grantz
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - Pauline Mendola
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY, USA.
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Tian ML, Jin Y, Du LY, Zhou GY, Zhang C, Ma GJ, Shi Y. Air pollution exposure during preconception and first trimester of pregnancy and gestational diabetes mellitus in a large pregnancy cohort, Hebei Province, China. Front Endocrinol (Lausanne) 2024; 15:1343172. [PMID: 39324126 PMCID: PMC11422764 DOI: 10.3389/fendo.2024.1343172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 08/26/2024] [Indexed: 09/27/2024] Open
Abstract
Objective To explore the relationship between the exposure level of particulate matter 2.5 (PM2.5) and particulate matter 10 (PM10) in the air of pregnant women during preconception and first trimester of pregnancy and the risk of gestational diabetes mellitus (GDM). Methods The data of pregnant women delivered in 22 monitoring hospitals in Hebei Province from 2019 to 2021 were collected, and the daily air quality data of their cities were used to calculate the exposure levels of PM2.5 and PM10 in different pregnancy stages, and logistic regression model was used to analyze the impact of exposure levels of PM2.5 and PM10 on GDM during preconception and first trimester of pregnancy. Results 108,429 singleton live deliveries were included in the study, of which 12,967 (12.0%) women had a GDM diagnosis. The prevalence of GDM increased over the course of the study from 10.2% (2019) to 14.9% (2021). From 2019 to 2021, the average exposure of PM2.5 and PM10 was relatively 56.67 and 103.08μg/m3 during the period of preconception and first trimester of pregnancy in Hebei Province. Handan, Shijiazhuang, and Xingtai regions had the most severe exposure to PM2.5 and PM10, while Zhangjiakou, Chengde, and Qinhuangdao had significantly lower exposure levels than other regions. The GDM group had statistically higher exposure concentrations of PM2.5 and PM10 during the period of preconception, first trimester, preconception and first trimester (P<0.05). Multivariate logistic regression analysis showed that the risk of GDM increases by 4.5%, 6.0%, and 10.6% for every 10ug/m3 increase in the average exposure value of PM2.5 in preconception, first trimester, preconception and first trimester, and 1.7%, 2.1%, and 3.9% for PM10. Moreover, High exposure to PM2.5 in the first, second, and third months of preconception and first trimester is associated with the risk of GDM. And high exposure to PM10 in the first, second, and third months of first trimester and the first, and third months of preconception is associated with the risk of GDM. Conclusion Exposure to high concentrations of PM2.5 and PM10 during preconception and first trimester of pregnancy can significantly increase the risk of GDM. It is important to take precautions to prevent exposure to pollutants, reduce the risk of GDM, and improve maternal and fetal outcomes.
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Affiliation(s)
- Mei-Ling Tian
- Department of Obstetrics and Gynecology, Hebei General Hospital, Shijiazhuang, China
| | - Ying Jin
- Department of Obstetrics and Gynecology, Hebei General Hospital, Shijiazhuang, China
| | - Li-Yan Du
- Department of Information Management, Hebei Center for Women and Children's Health, Shijiazhuang, China
| | - Gui-Yun Zhou
- Department of Obstetrics and Gynecology, Hebei Provincial Hospital of Chinese Medicine, Shijiazhuang, China
| | - Cui Zhang
- Department of Obstetrics and Gynecology, Hebei General Hospital, Shijiazhuang, China
| | - Guo-Juan Ma
- Department of Obstetrics and Gynecology, Hebei General Hospital, Shijiazhuang, China
| | - Yin Shi
- Department of Obstetrics and Gynecology, Hebei General Hospital, Shijiazhuang, China
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Liu W, Zou H, Liu W, Qin J. The impact of PM 2.5 and its constituents on gestational diabetes mellitus: a retrospective cohort study. BMC Public Health 2024; 24:2249. [PMID: 39160489 PMCID: PMC11334325 DOI: 10.1186/s12889-024-19767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Accepted: 08/12/2024] [Indexed: 08/21/2024] Open
Abstract
BACKGROUND There is increasing evidence that exposure to PM2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM2.5 constituents and the risk of GDM are still limited. METHODS A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed. RESULTS After adjustment for confounders, exposure to PM2.5 and its constituents (NO3-, NH4+, and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO3- and NH4+ occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118-1.293) and 18.2% (95% CI. 1.107-1.263), respectively. The lowest inflection points between PM2.5, SO42-, NO3-, NH4+, OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m3, respectively. In the first trimester, an age interaction effect between exposure to SO42-, OM, and BC and the risk of GDM was observed. CONCLUSIONS This study demonstrates a positive association between exposure to PM2.5 and its constituents and the risk of GDM. Specifically, exposure to NO3-, NH4+, and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM2.5 and its constituents on the risk of GDM.
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Affiliation(s)
- Weiqi Liu
- Department of Clinical Laboratory, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, 510800, Guangdong, People's Republic of China.
| | - Haidong Zou
- Department of Obstetrics, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, 510800, Guangdong, People's Republic of China
| | - Weiling Liu
- Department of Clinical Laboratory, Foshan Fosun Chancheng Hospital, Foshan, 528000, Guangdong, People's Republic of China
| | - Jiangxia Qin
- Department of Obstetrics, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, 510800, Guangdong, People's Republic of China
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Wan Z, Zhang S, Zhuang G, Liu W, Qiu C, Lai H, Liu W. Effect of fine particulate matter exposure on gestational diabetes mellitus risk: a retrospective cohort study. Eur J Public Health 2024; 34:787-793. [PMID: 38783609 PMCID: PMC11293809 DOI: 10.1093/eurpub/ckae094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND The literature on the association between fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM) risk has focused mainly on exposure during the first and second trimesters, and the research results are inconsistent. Therefore, this study aimed to investigate the associations between PM2.5 exposure during preconception, the first trimester and second trimester and GDM risk in pregnant women in Guangzhou. METHODS A retrospective cohort study of 26 354 pregnant women was conducted, estimating PM2.5, particulate matter with a diameter >10 µm (PM10), sulphur dioxide (SO2), carbon monoxide (CO) and ozone (O3) exposure during preconception and the first and second trimesters. Analyses were performed using Cox proportional hazards models and nonlinear distributed lag models. RESULTS The study found that exposure to PM2.5 or a combination of two pollutants (PM2.5+PM10, PM2.5+SO2, PM2.5+CO and PM2.5+O3) was found to be significantly associated with GDM risk (P < 0.05). In the second trimester, with significant interactions found for occupation and anaemia between PM2.5 and GDM. When the PM2.5 concentrations were ≥19.56, ≥25.69 and ≥23.87 μg/m3 during preconception and the first and second trimesters, respectively, the hazard ratio for GDM started to increase. The critical window for PM2.5 exposure was identified to be from 9 to 11 weeks before conception. CONCLUSIONS Our study results suggest that PM2.5 exposure during preconception and the first and second trimesters increases the risk of GDM, with the preconception period appearing to be the critical window for PM2.5 exposure.
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Affiliation(s)
- Zhenyan Wan
- Division of Neonatology, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, Guangdong, People’s Republic of China
| | - Shandan Zhang
- Division of Neonatology, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, Guangdong, People’s Republic of China
| | - Guiying Zhuang
- Division of Neonatology, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, Guangdong, People’s Republic of China
| | - Weiqi Liu
- Department of Clinical Laboratory, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, Guangdong, People’s Republic of China
| | - Cuiqing Qiu
- Medical Information Office, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, Guangdong, People’s Republic of China
| | - Huiqin Lai
- Department of Clinical Laboratory, Guanzhou Yuexiu Liurong Community Health Service Center, Guangzhou, Guangdong, People’s Republic of China
| | - Weiling Liu
- Department of Clinical Laboratory, Foshan Fosun Chancheng Hospital, Foshan, Guangdong, People’s Republic of China
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Chen Y, Wang Y, Chen Q, Chung MK, Liu Y, Lan M, Wei Y, Lin L, Cai L. Gestational and Postpartum Exposure to PM 2.5 Components and Glucose Metabolism in Chinese Women: A Prospective Cohort Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:8675-8684. [PMID: 38728584 DOI: 10.1021/acs.est.4c03087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Pregnant women are physiologically prone to glucose intolerance, while the puerperium represents a critical phase for recovery. However, how air pollution disrupts glucose homeostasis during the gestational and early postpartum periods remains unclear. This prospective cohort study conducted an oral glucose tolerance test and measured the insulin levels of 834 pregnant women in Guangzhou, with a follow-up for 443 puerperae at 6-8 weeks postpartum. Residential PM2.5 and five chemical components were estimated by an established spatiotemporal model. The adjusted linear model showed that an IQR increase in gestational PM2.5 exposure was associated with an increase of 0.17 mmol/L (95% CI: 0.06, 0.28) in fasting plasma glucose (FPG) and 0.24 (95% CI: 0.05, 0.42) in the insulin resistance index. Postpartum PM2.5 exposure was linked to a 0.17 mmol/L (95% CI: 0.05, 0.28) elevation in FPG per IQR, with a strengthened association found in women with gestational diabetes (Pinteraction = 0.003). In the quantile-based g-computation model, NO3- consistently contributed to the combined effect of PM2.5 components on gestational and postpartum FPG. This study was the first to suggest that PM2.5 components were associated with exacerbated gestational insulin resistance and elevated postpartum FPG. Targeted interventions reducing the emissions of toxic PM2.5 components are essential to improving maternal glucose metabolism.
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Affiliation(s)
- Yujing Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, 999077, China
| | - Yuxuan Wang
- Global Health Research Center, Duke Kunshan University, Kunshan 215316, Jiangsu, China
| | - Qian Chen
- Department of Neonatology, Guangzhou Key Laboratory of Neonatal Intestinal Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510080, Guangdong, China
| | - Ming Kei Chung
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, 999077, China
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong 999077, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong 999077, China
| | - Yu Liu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
| | - Minyan Lan
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
| | - Yanhong Wei
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080 Guangdong, China
| | - Lizi Lin
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
| | - Li Cai
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
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Hammer L, Heazell AEP, Povey A, Myers JE, Thompson JMD, Johnstone ED. Assessment of the association between ambient air pollution and stillbirth in the UK: Results from a secondary analysis of the MiNESS case-control study. BJOG 2024; 131:598-609. [PMID: 37880925 DOI: 10.1111/1471-0528.17696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 09/27/2023] [Accepted: 10/12/2023] [Indexed: 10/27/2023]
Abstract
OBJECTIVE We examined whether the risk of stillbirth was related to ambient air pollution in a UK population. DESIGN Prospective case-control study. SETTING Forty-one maternity units in the UK. POPULATION Women who had a stillbirth ≥28 weeks' gestation (n = 238) and women with an ongoing pregnancy at the time of interview (n = 597). METHODS Secondary analysis of data from the Midlands and North of England Stillbirth case-control study only including participants domiciled within 20 km of fixed air pollution monitoring stations. Pollution exposure was calculated using pollution climate modelling data for NO2 , NOx and PM2.5 . The association between air pollution exposure and stillbirth risk was assessed using multivariable logistic regression adjusting for household income, maternal body mass index (BMI), maternal smoking, Index of Multiple Deprivation quintile and household smoking and parity. MAIN OUTCOME MEASURE Stillbirth. RESULTS There was no association with whole pregnancy ambient air pollution exposure and stillbirth risk, but there was an association with preconceptual NO2 exposure (adjusted odds ratio [aOR] 1.06, 95% CI 1.01-1.08 per microg/m3 ). Risk of stillbirth was associated with maternal smoking (aOR 2.54, 95% CI 1.38-4.71), nulliparity (aOR 2.16, 95% CI 1.55-3.00), maternal BMI (aOR 1.05, 95% CI 1.01-1.08) and placental abnormalities (aOR 4.07, 95% CI 2.57-6.43). CONCLUSIONS Levels of ambient air pollution exposure during pregnancy in the UK, all of were beneath recommended thresholds, are not associated with an increased risk of stillbirth. Periconceptual exposure to NO2 may be associated with increased risk but further work is required to investigate this association.
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Affiliation(s)
- Lucy Hammer
- Maternal and Fetal Health Research Centre, Division of Developmental Biology and Medicine, University of Manchester, Manchester, UK
| | - Alexander E P Heazell
- Maternal and Fetal Health Research Centre, Division of Developmental Biology and Medicine, University of Manchester, Manchester, UK
- Saint Mary's Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Science Centre, Manchester, UK
| | - Andrew Povey
- Centre for Occupational and Environmental Health, Division of Population Health, Health Services Research and Primary Care, University of Manchester, Manchester, UK
| | - Jenny E Myers
- Maternal and Fetal Health Research Centre, Division of Developmental Biology and Medicine, University of Manchester, Manchester, UK
- Saint Mary's Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Science Centre, Manchester, UK
| | - John M D Thompson
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Paediatrics: Child Health and Youth Health, University of Auckland, Auckland, New Zealand
| | - Edward D Johnstone
- Maternal and Fetal Health Research Centre, Division of Developmental Biology and Medicine, University of Manchester, Manchester, UK
- Saint Mary's Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Science Centre, Manchester, UK
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Zhu K, Mendola P, Barnabei VM, Wang M, Hageman Blair R, Schwartz J, Shelton J, Lei L, Mu L. Association of prenatal exposure to PM 2.5 and NO 2 with gestational diabetes in Western New York. ENVIRONMENTAL RESEARCH 2024; 244:117873. [PMID: 38072106 DOI: 10.1016/j.envres.2023.117873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 11/20/2023] [Accepted: 12/03/2023] [Indexed: 12/24/2023]
Abstract
BACKGROUND Although many studies have examined the association between prenatal air pollution exposure and gestational diabetes (GDM), the relevant exposure windows remain inconclusive. We aim to examine the association between preconception and trimester-specific exposure to PM2.5 and NO2 and GDM risk and explore modifying effects of maternal age, pre-pregnancy body mass index (BMI), smoking, exercise during pregnancy, race and ethnicity, and neighborhood disadvantage. METHODS Analyses included 192,508 birth records of singletons born to women without pre-existing diabetes in Western New York, 2004-2016. Daily PM2.5 and NO2 at 1-km2 grids were estimated from ensemble-based models. We assigned each birth with exposures averaged in preconception and each trimester based on residential zip-codes. We used logistic regression to examine the associations and distributed lag models (DLMs) to explore the sensitive windows by month. Relative excess risk due to interaction (RERI) and multiplicative interaction terms were calculated. RESULTS GDM was associated with PM2.5 averaged in the first two trimesters (per 2.5 μg/m3: OR = 1.08, 95% CI: 1.01, 1.14) or from preconception to the second trimester (per 2.5 μg/m3: OR = 1.10, 95% CI: 1.03, 1.18). NO2 exposure during each averaging period was associated with GDM risk (per 10 ppb, preconception: OR = 1.10, 95% CI: 1.06, 1.14; first trimester: OR = 1.12, 95% CI: 1.08, 1.16; second trimester: OR = 1.10, 95% CI: 1.06, 1.14). In DLMs, sensitive windows were identified in the 5th and 6th gestational months for PM2.5 and one month before and three months after conception for NO2. Evidence of interaction was identified for pre-pregnancy BMI with PM2.5 (P-for-interaction = 0.023; RERI = 0.21, 95% CI: 0.10, 0.33) and with NO2 (P-for-interaction = 0.164; RERI = 0.16, 95% CI: 0.04, 0.27). CONCLUSION PM2.5 and NO2 exposure may increase GDM risk, and sensitive windows may be the late second trimester for PM2.5 and periconception for NO2. Women with higher pre-pregnancy BMI may be more susceptible to exposure effects.
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Affiliation(s)
- Kexin Zhu
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Pauline Mendola
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Vanessa M Barnabei
- Department of Obstetrics and Gynecology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Rachael Hageman Blair
- Department of Biostatistics, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - James Shelton
- Department of Obstetrics and Gynecology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Lijian Lei
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Lina Mu
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA.
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Zeng X, Zhan Y, Zhou W, Qiu Z, Wang T, Chen Q, Qu D, Huang Q, Cao J, Zhou N. The Influence of Airborne Particulate Matter on the Risk of Gestational Diabetes Mellitus: A Large Retrospective Study in Chongqing, China. TOXICS 2023; 12:19. [PMID: 38250975 PMCID: PMC10818620 DOI: 10.3390/toxics12010019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/17/2023] [Accepted: 12/21/2023] [Indexed: 01/23/2024]
Abstract
Emerging research findings suggest that airborne particulate matter might be a risk factor for gestational diabetes mellitus (GDM). However, the concentration-response relationships and the susceptible time windows for different types of particulate matter may vary. In this retrospective analysis, we employ a novel robust approach to assess the crucial time windows regarding the prevalence of GDM and to distinguish the susceptibility of three GDM subtypes to air pollution exposure. This study included 16,303 pregnant women who received routine antenatal care in 2018-2021 at the Maternal and Child Health Hospital in Chongqing, China. In total, 2482 women (15.2%) were diagnosed with GDM. We assessed the individual daily average exposure to air pollution, including PM2.5, PM10, O3, NO2, SO2, and CO based on the volunteers' addresses. We used high-accuracy gridded air pollution data generated by machine learning models to assess particulate matter per maternal exposure levels. We further analyzed the association of pre-pregnancy, early, and mid-pregnancy exposure to environmental pollutants using a generalized additive model (GAM) and distributed lag nonlinear models (DLNMs) to analyze the association between exposure at specific gestational weeks and the risk of GDM. We observed that, during the first trimester, per IQR increases for PM10 and PM2.5 exposure were associated with increased GDM risk (PM10: OR = 1.19, 95%CI: 1.07~1.33; PM2.5: OR = 1.32, 95%CI: 1.15~1.50) and isolated post-load hyperglycemia (GDM-IPH) risk (PM10: OR = 1.23, 95%CI: 1.09~1.39; PM2.5: OR = 1.38, 95%CI: 1.18~1.61). Second-trimester O3 exposure was positively correlated with the associated risk of GDM, while pre-pregnancy and first-trimester exposure was negatively associated with the risk of GDM-IPH. Exposure to SO2 in the second trimester was negatively associated with the risk of GDM-IPH. However, there were no observed associations between NO2 and CO exposure and the risk of GDM and its subgroups. Our results suggest that maternal exposure to particulate matter during early pregnancy and exposure to O3 in the second trimester might increase the risk of GDM, and GDM-IPH is the susceptible GDM subtype to airborne particulate matter exposure.
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Affiliation(s)
- Xiaoling Zeng
- Institute of Toxicology, Facutly of Military Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China; (X.Z.); (T.W.); (Q.C.)
- School of Public Health, China Medical University, Shenyang 110122, China
| | - Yu Zhan
- Department of Environmental Science and Engineering, Sichuan University, Chengdu 610065, China; (Y.Z.); (Z.Q.)
| | - Wei Zhou
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children’s Hospital of Chongqing Medical University), Chongqing 401147, China; (W.Z.); (Q.H.)
| | - Zhimei Qiu
- Department of Environmental Science and Engineering, Sichuan University, Chengdu 610065, China; (Y.Z.); (Z.Q.)
| | - Tong Wang
- Institute of Toxicology, Facutly of Military Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China; (X.Z.); (T.W.); (Q.C.)
| | - Qing Chen
- Institute of Toxicology, Facutly of Military Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China; (X.Z.); (T.W.); (Q.C.)
| | - Dandan Qu
- Clinical Research Centre, Women and Children’s Hospital of Chongqing Medical University, Chongqing 401147, China;
- Chongqing Research Centre for Prevention & Control of Maternal and Child Diseases and Public Health, Women and Children’s Hospital of Chongqing Medical University, Chongqing 401147, China
| | - Qiao Huang
- Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children’s Hospital of Chongqing Medical University), Chongqing 401147, China; (W.Z.); (Q.H.)
| | - Jia Cao
- Institute of Toxicology, Facutly of Military Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China; (X.Z.); (T.W.); (Q.C.)
| | - Niya Zhou
- Clinical Research Centre, Women and Children’s Hospital of Chongqing Medical University, Chongqing 401147, China;
- Chongqing Research Centre for Prevention & Control of Maternal and Child Diseases and Public Health, Women and Children’s Hospital of Chongqing Medical University, Chongqing 401147, China
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10
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Mínguez-Alarcón L, Chagnon O, Tanaka A, Williams PL, James-Todd T, Ford JB, Souter I, Rexrode KM, Hauser R, Chavarro JE. Preconception Stress and Pregnancy Serum Glucose Levels Among Women Attending a Fertility Center. J Endocr Soc 2023; 8:bvad152. [PMID: 38178907 PMCID: PMC10766068 DOI: 10.1210/jendso/bvad152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Indexed: 01/06/2024] Open
Abstract
Context The association between women's stress and pregnancy glucose levels remain unclear, specifically when considering the preconception period as a sensitive window of exposure. Objective We investigated whether preconception perceived stress was associated with glucose levels during pregnancy among women attending a fertility center (2004-2019). Methods Before conception, women completed a psychological stress survey using the short version of the validated Perceived Stress Scale 4 (PSS-4), and blood glucose was measured using a 50-gram glucose load test during late pregnancy as a part of screening for gestational diabetes. Linear and log-binomial regression models were used to assess associations of total PSS-4 scores with mean glucose levels and abnormal glucose levels ( ≥ 140 mg/dL), adjusting for age, body mass index, race, smoking, education, physical activity, primary infertility diagnosis, number of babies, and mode of conception. Results Psychological stress was positively associated with mean abnormal glucose levels. The adjusted marginal means (95% CI) of mean glucose levels for women in the first, second, and third tertiles of psychological stress were 115 (110, 119), 119 (115, 123), and 124 (119, 128), and mg/dL, respectively (P for trend = .007). Also, women in the second and third tertiles of psychological stress had 4% and 13% higher probabilities of having abnormal glucose compared with women in the first tertile of psychological stress (P trend = .01). Conclusion These results highlight the importance of considering preconception when evaluating the relationship between women's stress and pregnancy glucose levels.
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Affiliation(s)
- Lidia Mínguez-Alarcón
- Channing Division of Network Medicine, Harvard Medical School & Brigham and Women's Hospital, Boston 02115, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA
| | - Olivia Chagnon
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA
| | - Aya Tanaka
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, USA
| | - Paige L Williams
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston 02115, USA
| | - Tamarra James-Todd
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, USA
| | - Jennifer B Ford
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA
| | - Irene Souter
- Division of Reproductive Medicine and IVF, Department of Obstetrics and Gynecology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Kathryn M Rexrode
- Division of Women's Health, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, USA
- Department of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School, Boston 02115, USA
| | - Jorge E Chavarro
- Channing Division of Network Medicine, Harvard Medical School & Brigham and Women's Hospital, Boston 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, USA
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11
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Jeong Y, Park S, Kwon E, Hur YM, You YA, Kim SM, Lee G, Lee KA, Kim SJ, Cho GJ, Oh MJ, Na SH, Lee SJ, Bae JG, Kim YH, Lee SJ, Kim YH, Kim YJ. Personal exposure of PM 2.5 and metabolic syndrome markers of pregnant women in South Korea: APPO study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:123893-123906. [PMID: 37996573 PMCID: PMC10746774 DOI: 10.1007/s11356-023-30921-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 11/02/2023] [Indexed: 11/25/2023]
Abstract
We examined the association between exposure to PM2.5, focused on individual exposure level, and metabolic dysfunction during pregnancy. APPO study (Air Pollution on Pregnancy Outcome) was a prospective, multicenter, observational cohort study conducted from January 2021 to March 2023. Individual PM2.5 concentrations were calculated using a time-weighted average model. Metabolic dysfunction during pregnancy was assessed based on a modified definition of metabolic syndrome and its components, accounting for pregnancy-specific criteria. Exposure to PM2.5 during pregnancy was associated with worsened metabolic parameters especially glucose metabolism. In comparison to participants exposed to the low PM2.5 group, those exposed to high PM2.5 levels exhibited increased odds of gestational diabetes mellitus (GDM) after adjusting for confounding variables in different adjusted models. Specifically, in model 1, the adjusted odds ratio (aOR) was 3.117 with a 95% confidence interval (CI) of 1.234-7.870; in model 2, the aOR was 3.855 with a 95% CI of 1.255-11.844; in model 3, the aOR was 3.404 with a 95% CI of 1.206-9.607; and in model 4, the aOR was 2.741 with a 95% CI of 0.712-10.547. Exposure to higher levels of PM2.5 during pregnancy was associated with a tendency to worsen metabolic dysfunction markers specifically in glucose homeostasis. Further research is needed to investigate the mechanisms underlying the effects of ambient PM2.5 on metabolic dysfunction during pregnancy.
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Affiliation(s)
- Yeonseong Jeong
- Department of Obstetrics and Gynecology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sunwha Park
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Medical Research Institute, Ewha Womans University Mokdong Hospital, Seoul, Korea
| | - Eunjin Kwon
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Medical Research Institute, Ewha Womans University Mokdong Hospital, Seoul, Korea
| | - Young Min Hur
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Medical Research Institute, Ewha Womans University Mokdong Hospital, Seoul, Korea
| | - Young-Ah You
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Medical Research Institute, Ewha Womans University Mokdong Hospital, Seoul, Korea
| | - Soo Min Kim
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Medical Research Institute, Ewha Womans University Mokdong Hospital, Seoul, Korea
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
| | - Gain Lee
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Medical Research Institute, Ewha Womans University Mokdong Hospital, Seoul, Korea
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
| | - Kyung A Lee
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Womans University Seoul Hospital, Seoul, Korea
| | - Soo Jung Kim
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Womans University Seoul Hospital, Seoul, Korea
| | - Geum Joon Cho
- Department of Obstetrics and Gynecology, College of Medicine, Korea University Guro Hospital, Seoul, Korea
| | - Min-Jeong Oh
- Department of Obstetrics and Gynecology, College of Medicine, Korea University Guro Hospital, Seoul, Korea
| | - Sung Hun Na
- Department of Obstetrics and Gynecology, College of Medicine, Kangwon National University Hospital, Chuncheon, Korea
| | - Se Jin Lee
- Department of Obstetrics and Gynecology, College of Medicine, Kangwon National University Hospital, Chuncheon, Korea
| | - Jin-Gon Bae
- Department of Obstetrics and Gynecology, College of Medicine, Keimyung University Dongsan Medical Center, Daegu, Korea
| | - Yu-Hwan Kim
- Department of Obstetrics and Gynecology, College of Medicine, Keimyung University Dongsan Medical Center, Daegu, Korea
| | - Soo-Jeong Lee
- Department of Obstetrics and Gynecology, Ulsan university hospital, University of Ulsan College of Medicine Ulsan, Ulsan, Korea
| | - Young-Han Kim
- Department of Obstetrics and Gynecology, Institute of Women's Life Medical Science, Yonsei University College of Medicine, Yonsei University Health System, Seoul, Republic of Korea
| | - Young Ju Kim
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Medical Research Institute, Ewha Womans University Mokdong Hospital, Seoul, Korea.
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Republic of Korea.
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12
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Zu P, Zhou L, Yin W, Zhang L, Wang H, Xu J, Jiang X, Zhang Y, Tao R, Zhu P. Association between exposure to air pollution during preconception and risk of gestational diabetes mellitus: The role of anti-inflammatory diet. ENVIRONMENTAL RESEARCH 2023; 235:116561. [PMID: 37479213 DOI: 10.1016/j.envres.2023.116561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/13/2023] [Accepted: 07/04/2023] [Indexed: 07/23/2023]
Abstract
BACKGROUND Regarding the association between the sensitive time-windows of air pollution (AP) exposure and gestational diabetes mellitus (GDM), epidemiological findings are inconsistent. The dietary inflammatory potential has been implicated in the development of GDM, but it is unclear whether an anti-inflammatory diet during pregnancy reduces the association between AP and GDM. OBJECTIVE We aimed to characterize the sensitive time-windows of AP to GDM risk. Further, to verify whether a maternal anti-inflammatory diet can reduce the risk of AP-induced GDM, by inhibiting inflammation. METHODS A total of 8495 pregnant women were included between 2015 and 2021 in the Maternal & Infants Health in Hefei study. Weekly mean AP exposure to fine particles (PM2.5 and PM10), SO2, and NO2 was estimated from the data of Hefei City Ecology and Environment Bureau. High-sensitivity C-reactive protein (hs-CRP) concentrations were measured to evaluate systemic inflammation. The empirical dietary inflammatory pattern (EDIP) score based on a validated food frequency questionnaire was used to assess the dietary inflammatory potential of pregnant women. Logistic regression models with distributed lags were used to identify the sensitive time-window for the effect of AP on GDM. Mediation analysis estimated the mediated effect of hs-CRP, linking AP with GDM. Stratified analysis was used to investigate the potential effect of anti-inflammatory diet on GDM risk. RESULTS The increased risks of GDM were found to be positively associated with exposure to PM2.5 (OR = 1.11, 95% CI:1.07-1.15), PM10 (OR = 1.12, 95% CI:1.09-1.16), and SO2 (OR = 1.42, 95% CI:1.25-1.60) by distributed lag models, and the critical exposure windows were 21st to 28th weeks of preconception. The proportion of association between PM2.5, PM10, and SO2 with GDM mediated by hs-CRP was 25.9%, 21.1%, and 19.4%, respectively, according to mediation analysis. In the stratified analyses by EDIP, the association between AP and GDM was not statistically significant among women those with anti-inflammatory diets. CONCLUSIONS Exposure to AP, especially in 21st to 28th week of preconception, is associated with risk of GDM, which is partly mediated by hs-CRP. Adherence to the anti-inflammatory dietary pattern may reduce the risk of AP-induced GDM.
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Affiliation(s)
- Ping Zu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China; MOE Key Laboratory of Population Health Across Life Cycle, Hefei, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China; Anhui Provincial Key Laboratory of Population Health and Aristogenic, Anhui Medical University, Hefei, China
| | - Liqi Zhou
- Department of Data Science/ Data Science and Big Data Technology, Shanghai University of International Business and Economics, Shanghai, China
| | - Wanjun Yin
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China; MOE Key Laboratory of Population Health Across Life Cycle, Hefei, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China; Anhui Provincial Key Laboratory of Population Health and Aristogenic, Anhui Medical University, Hefei, China
| | - Lei Zhang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China; MOE Key Laboratory of Population Health Across Life Cycle, Hefei, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China; Anhui Provincial Key Laboratory of Population Health and Aristogenic, Anhui Medical University, Hefei, China
| | - Haixia Wang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China; MOE Key Laboratory of Population Health Across Life Cycle, Hefei, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China; Anhui Provincial Key Laboratory of Population Health and Aristogenic, Anhui Medical University, Hefei, China
| | - Jirong Xu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China; MOE Key Laboratory of Population Health Across Life Cycle, Hefei, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China; Anhui Provincial Key Laboratory of Population Health and Aristogenic, Anhui Medical University, Hefei, China
| | - Xiaomin Jiang
- Department of Obstetrics and Gynecology, Anhui Women and Child Health Care Hospital, Hefei, China
| | - Ying Zhang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ruixue Tao
- Department of Gynecology and Obstetrics, Hefei First People's Hospital, Hefei, China
| | - Peng Zhu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China; MOE Key Laboratory of Population Health Across Life Cycle, Hefei, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China; Anhui Provincial Key Laboratory of Population Health and Aristogenic, Anhui Medical University, Hefei, China.
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13
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Decrue F, Townsend R, Miller MR, Newby DE, Reynolds RM. Ambient air pollution and maternal cardiovascular health in pregnancy. Heart 2023; 109:1586-1593. [PMID: 37217298 DOI: 10.1136/heartjnl-2022-322259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/18/2023] [Indexed: 05/24/2023] Open
Abstract
In this review, we summarise the current epidemiological and experimental evidence on the association of ambient (outdoor) air pollution exposure and maternal cardiovascular health during pregnancy. This topic is of utmost clinical and public health importance as pregnant women represent a potentially susceptible group due to the delicate balance of the feto-placental circulation, rapid fetal development and tremendous physiological adaptations to the maternal cardiorespiratory system during pregnancy.Several meta-analyses including up to 4 245 170 participants provide robust evidence that air pollutants, including particulate matter, nitrogen oxides and others, have adverse effects on the development of hypertensive disorders of pregnancy, gestational diabetes mellitus and cardiovascular events during labour. Potential underlying biological mechanisms include oxidative stress with subsequent endothelial dysfunction and vascular inflammation, β-cell dysfunction and epigenetic changes. Endothelial dysfunction can lead to hypertension by impairing vasodilatation and promoting vasoconstriction. Air pollution and the consequent oxidative stress can additionally accelerate β-cell dysfunction, which in turn triggers insulin resistance leading to gestational diabetes mellitus. Epigenetic changes in placental and mitochondrial DNA following air pollution exposures can lead to altered gene expression and contribute to placental dysfunction and induction of hypertensive disorders of pregnancy.The maternal and fetal consequences of such cardiovascular and cardiometabolic disease during pregnancy can be serious and long lasting, including preterm birth, increased risk of type 2 diabetes mellitus or cardiovascular disease later in life. Acceleration of efforts to reduce air pollution is therefore urgently needed to realise the full health benefits for pregnant mothers and their children.
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Affiliation(s)
- Fabienne Decrue
- Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK
| | - Rosemary Townsend
- Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK
| | - Mark R Miller
- Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK
| | - David E Newby
- Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK
| | - Rebecca M Reynolds
- Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK
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14
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Harper T, Kuohung W, Sayres L, Willis MD, Wise LA. Optimizing preconception care and interventions for improved population health. Fertil Steril 2023; 120:438-448. [PMID: 36516911 DOI: 10.1016/j.fertnstert.2022.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/18/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022]
Abstract
There is growing literature indicating that optimal preconception health is associated with improved reproductive, perinatal, and pediatric outcomes. Given that preconception care is recommended for all individuals planning a pregnancy, medical providers and public health practitioners have a unique opportunity to optimize care and improve health outcomes for reproductive-aged individuals. Knowledge of the determinants of preconception health is important for all types of health professionals, including policy makers. Although some evidence-based recommendations have already been implemented, additional research is needed to identify factors associated with favorable health outcomes and to ensure that effective interventions are made in a timely fashion. Given the largely clinical readership of this journal, this piece is primarily focused on clinical care. However, we acknowledge that optimizing preconception health for the entire population at risk of pregnancy requires broadening our strategies to include population-health interventions that consider the larger social systems, structures, and policies that shape individual health outcomes.
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Affiliation(s)
- Teresa Harper
- Division of Maternal and Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado School of Medicine, Aurora, Colorado.
| | - Wendy Kuohung
- Division of Reproductive Endocrinology, Department of Obstetrics and Gynecology, Boston University School of Medicine, Boston, Massachusetts
| | - Lauren Sayres
- Division of Maternal and Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado School of Medicine, Aurora, Colorado
| | - Mary D Willis
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - Lauren A Wise
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
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15
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Cao L, Diao R, Shi X, Cao L, Gong Z, Zhang X, Yan X, Wang T, Mao H. Effects of Air Pollution Exposure during Preconception and Pregnancy on Gestational Diabetes Mellitus. TOXICS 2023; 11:728. [PMID: 37755739 PMCID: PMC10534707 DOI: 10.3390/toxics11090728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 09/28/2023]
Abstract
This study aimed to investigate the association between air pollution and gestational diabetes mellitus (GDM) in small- and medium-sized cities, identify sensitive periods and major pollutants, and explore the effects of air pollution on different populations. A total of 9820 women who delivered in Handan Maternal and Child Health Hospital in the Hebei Province from February 2018 to July 2020 were included in the study. Logistic regression and principal component logistic regression models were used to assess the effects of air pollution exposure during preconception and pregnancy on GDM risk and the differences in the effects across populations. The results suggested that each 20 μg/m3 increase in PM2.5 and PM10 exposure during preconception and pregnancy significantly increased the risk of GDM, and a 10 μg/m3 increase in NO2 exposure during pregnancy was also associated with the risk of GDM. In a subgroup analysis, pregnant women aged 30-35 years, nulliparous women, and those with less than a bachelor's education were the most sensitive groups. This study provides evidence for an association between air pollution and the prevalence of GDM, with PM2.5, PM10, and NO2 as risk factors for GDM.
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Affiliation(s)
- Lei Cao
- China Institute for Radiation Protection, Taiyuan 030006, China
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key, Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Ruiping Diao
- Handan Maternal and Children Health Hospital, Handan 056001, China
| | - Xuefeng Shi
- China Institute for Radiation Protection, Taiyuan 030006, China
| | - Lu Cao
- China Institute for Radiation Protection, Taiyuan 030006, China
| | - Zerui Gong
- China Institute for Radiation Protection, Taiyuan 030006, China
| | - Xupeng Zhang
- China Institute for Radiation Protection, Taiyuan 030006, China
| | - Xiaohan Yan
- China Institute for Radiation Protection, Taiyuan 030006, China
| | - Ting Wang
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key, Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Hongjun Mao
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key, Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
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16
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Huang Y, Wu S, Luo H, Yang Y, Xu J, Zhang Y, Wang Q, Shen H, Zhang Y, Yan D, Jiang L, Zhang H, Chen R, Kan H, Cai J, He Y, Ma X. Association of Fine Particulate Matter and Its Components with Macrosomia: A Nationwide Birth Cohort Study of 336 Chinese Cities. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:11465-11475. [PMID: 37493575 DOI: 10.1021/acs.est.3c03280] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
To examine the associations between macrosomia risk and exposure to fine particulate matter (PM2.5) and its chemical components during pregnancy, we collected birth records between 2010 and 2015 in mainland China from the National Free Preconception Health Examination Project and used satellite-based models to estimate concentrations of PM2.5 mass and five main components, namely, black carbon (BC), organic carbon (OC), nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+). Associations between macrosomia risk and prenatal exposure to PM2.5 were examined by logistic regression analysis, and the sensitive subgroups were explored by stratified analyses. Of the 3,248,263 singleton newborns from 336 cities, 165,119 (5.1%) had macrosomia. Each interquartile range increase in concentration of PM2.5 during the entire pregnancy was associated with increased risk of macrosomia (odds ratio (OR) = 1.18; 95% confidence interval (CI), 1.17-1.20). Among specific components, the largest effect estimates were found on NO3- (OR = 1.36; 95% CI, 1.35-1.38) followed by OC (OR = 1.23; 95% CI, 1.22-1.24), NH4+ (OR = 1.22; 95% CI, 1.21-1.23), and BC (OR = 1.21; 95% CI, 1.20-1.22). We also that found boys, women with a normal or lower prepregnancy body mass index, and women with irregular or no folic acid supplementation experienced higher risk of macrosomia associated with PM2.5 exposure.
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Affiliation(s)
- Yuxin Huang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Shenpeng Wu
- National Human Genetic Resources Center, National Research Institute for Family Planning, Beijing 100081, China
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Huihuan Luo
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Ying Yang
- National Human Genetic Resources Center, National Research Institute for Family Planning, Beijing 100081, China
| | - Jihong Xu
- National Human Genetic Resources Center, National Research Institute for Family Planning, Beijing 100081, China
| | - Ya Zhang
- National Human Genetic Resources Center, National Research Institute for Family Planning, Beijing 100081, China
| | - Qiaomei Wang
- Department of Maternal and Child Health, National Health Commission of the People's Republic of China, Beijing 100088, China
| | - Haiping Shen
- Department of Maternal and Child Health, National Health Commission of the People's Republic of China, Beijing 100088, China
| | - Yiping Zhang
- Department of Maternal and Child Health, National Health Commission of the People's Republic of China, Beijing 100088, China
| | - Donghai Yan
- Department of Maternal and Child Health, National Health Commission of the People's Republic of China, Beijing 100088, China
| | - Lifang Jiang
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan 450002, China
| | - Hongping Zhang
- Wenzhou People's Hospital/Wenzhou Maternal and Child Health Care Hospital/The Third Clinical Institute Affiliated to Wenzhou Medical University/The Third Affiliated Hospital of Shanghai University, Wenzhou, Zhejiang 325000, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Jing Cai
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Yuan He
- National Human Genetic Resources Center, National Research Institute for Family Planning, Beijing 100081, China
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Xu Ma
- National Human Genetic Resources Center, National Research Institute for Family Planning, Beijing 100081, China
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
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Pavuk M, Rosenbaum PF, Lewin MD, Serio TC, Rago P, Cave MC, Birnbaum LS. Polychlorinated biphenyls, polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, pesticides, and diabetes in the Anniston Community Health Survey follow-up (ACHS II): single exposure and mixture analysis approaches. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 877:162920. [PMID: 36934946 DOI: 10.1016/j.scitotenv.2023.162920] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/24/2023] [Accepted: 03/13/2023] [Indexed: 05/06/2023]
Abstract
Dioxins and dioxin-like compounds measurements were added to polychlorinated biphenyls (PCBs) and organochlorine pesticides to expand the exposure profile in a follow-up to the Anniston Community Health Survey (ACHS II, 2014) and to study diabetes associations. Participants of ACHS I (2005-2007) still living within the study area were eligible to participate in ACHS II. Diabetes status (type-2) was determined by a doctor's diagnosis, fasting glucose ≥125 mg/dL, or being on any glycemic control medication. Incident diabetes cases were identified in ACHS II among those who did not have diabetes in ACHS I, using the same criteria. Thirty-five ortho-substituted PCBs, 6 pesticides, 7 polychlorinated dibenzo-p-dioxins (PCDD), 10 furans (PCDF), and 3 non-ortho PCBs were measured in 338 ACHS II participants. Dioxin toxic equivalents (TEQs) were calculated for all dioxin-like compounds. Main analyses used logistic regression models to calculate odds ratios (OR) and 95 % confidence intervals (CI). In models adjusted for age, race, sex, BMI, total lipids, family history of diabetes, and taking lipid lowering medication, the highest ORs for diabetes were observed for PCDD TEQ: 3.61 (95 % CI: 1.04, 12.46), dichloro-diphenyl dichloroethylene (p,p'-DDE): 2.07 (95 % CI 1.08, 3.97), and trans-Nonachlor: 2.55 (95 % CI 0.93, 7.02). The OR for sum 35 PCBs was 1.22 (95 % CI: 0.58-2.57). To complement the main analyses, we used BKMR and g-computation models to evaluate 12 mixture components including 4 TEQs, 2 PCB subsets and 6 pesticides; suggestive positive associations for the joint effect of the mixture analyses resulted in ORs of 1.40 (95% CI: -1.13, 3.93) for BKMR and 1.32 (95% CI: -1.12, 3.76) for g-computation. The mixture analyses provide further support to previously observed associations of trans-Nonachlor, p,p'- DDE, PCDD TEQ and some PCB groups with diabetes.
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Affiliation(s)
- M Pavuk
- Agency for Toxic Substances and Disease Registry (ATSDR), Centers for Disease Control and Prevention (CDC), Atlanta, GA, United States of America
| | - P F Rosenbaum
- SUNY Upstate Medical University, Syracuse, NY, United States of America.
| | - M D Lewin
- Agency for Toxic Substances and Disease Registry (ATSDR), Centers for Disease Control and Prevention (CDC), Atlanta, GA, United States of America
| | - T C Serio
- Agency for Toxic Substances and Disease Registry (ATSDR), Centers for Disease Control and Prevention (CDC), Atlanta, GA, United States of America; ATSDR/CDC, Atlanta, GA, United States of America
| | - P Rago
- ATSDR/CDC, Atlanta, GA, United States of America
| | - M C Cave
- University of Louisville, Louisville, KY, United States of America
| | - L S Birnbaum
- NIEHS, Research Triangle Park, NC, United States of America
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18
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Yang X, Zhang Q, Sun Y, Li C, Zhou H, Jiang C, Li J, Zhang L, Chen X, Tang N. Joint effect of ambient PM 2.5 exposure and vitamin B 12 during pregnancy on the risk of gestational diabetes mellitus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 876:162514. [PMID: 36868273 DOI: 10.1016/j.scitotenv.2023.162514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/23/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Evidence has indicated that the risk of gestational diabetes mellitus (GDM) was linked to PM2.5 exposure during pregnancy, but findings on susceptible exposure windows are inconsistent. Further, previous studies have not paid attention to B12 intake in the relationship between PM2.5 exposure and GDM. The study is aimed to identify the strength and exposure periods for associations of PM2.5 exposure with GDM, followed by exploring the potential interplay of gestational B12 levels and PM2.5 exposure on the risk of GDM. METHODS The participants were recruited in a birth cohort between 2017 and 2018, and 1396 eligible pregnant women who completed a 75-g oral glucose tolerance test (OGTT) were included. Prenatal PM2.5 concentrations were estimated using an established spatiotemporal model. Logistic and linear regression analyses were used to test associations of gestational PM2.5 exposure with GDM and OGTT-glucose levels, respectively. The joint associations of gestational PM2.5 exposure and B12 level on GDM were examined under crossed exposure combinations of PM2.5 (high versus low) and B12 (insufficient versus sufficient). RESULTS In the 1396 pregnant women, the median levels of PM2.5 exposure during the 12 weeks before pregnancy, the 1st trimester, and the 2nd trimesters were 59.33 μg/m3, 63.44 μg/m3, and 64.39 μg/m3, respectively. The risk of GDM was significantly associated with a 10 μg/m3 increase of PM2.5 during the 2nd trimester (RR = 1.44, 95 % CI: 1.01, 2.04). The percentage change in fasting glucose was also associated with PM2.5 exposure during the 2nd trimester. A higher risk of GDM was observed among women with high PM2.5 exposure and insufficient B12 levels than those with low PM2.5 and sufficient B12. CONCLUSION The study supported higher PM2.5 exposure during the 2nd trimester is significantly associated with GDM risk. It first highlighted insufficient B12 status might enhance adverse effects of air pollution on GDM.
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Affiliation(s)
- Xueli Yang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Qiang Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Yao Sun
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Chen Li
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Hongyu Zhou
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Chang Jiang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Jing Li
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China; Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Liwen Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Xi Chen
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Naijun Tang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China.
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Gong Z, Yue H, Li Z, Bai S, Cheng Z, He J, Wang H, Li G, Sang N. Association between maternal exposure to air pollution and gestational diabetes mellitus in Taiyuan, North China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 875:162515. [PMID: 36868286 DOI: 10.1016/j.scitotenv.2023.162515] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 02/22/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND The effect of air pollution on human health has been a major concern, especially the association between air pollution and gestational diabetes mellitus (GDM). METHODS In this study, we conducted a retrospective cohort study in Taiyuan, a typical energy production base in China. This study included 28,977 pairs of mothers and infants between January 2018 and December 2020. To screen for GDM, oral glucose tolerance test (OGTT) was performed in pregnant women at 24-28 weeks of gestation. Logistic regression was used to assess the trimester-specific association between 5 common air pollutants (PM10, PM2.5, NO2, SO2, and O3) and GDM, and the weekly-based association was also assessed using distributed lag non-linear models (DLNMs). Odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated for the association between GDM and each air pollutant. RESULTS The overall incidence of GDM was 3.29 %. PM2.5 was positively associated with GDM over the second trimester (OR [95 % CI], 1.105 [1.021, 1.196]). O3 was positively associated with GDM in the preconception period (OR [95 % CI], 1.125 [1.024, 1.236]), the first trimester (OR [95 % CI], 1.088 [1.019, 1.161]) and the 1st + 2nd trimester (OR [95 % CI], 1.643 [1.387, 1.945]). For the weekly-based association, PM2.5 was positively associated with GDM at 19-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.044 [1.021, 1.067]). PM10 was positively associated with GDM at 18-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.016 [1.003, 1.030]). O3 was positively associated with GDM during the 3rd week before conception to the 8th gestational week, with the strongest association at week 3 of gestation (OR [95 % CI], 1.054 [1.032, 1.077]). CONCLUSION The findings are important for the development of effective air quality policies and the optimization of preventive strategies for preconception and prenatal care.
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Affiliation(s)
- Zhihua Gong
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China; Department of Clinical Laboratory, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi 030032, PR China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China
| | - Huifeng Yue
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Zhihong Li
- Taiyuan Taihang Hospital, Taiyuan, Shanxi 030006, PR China
| | - Shuqing Bai
- Taiyuan Taihang Hospital, Taiyuan, Shanxi 030006, PR China
| | - Zhonghui Cheng
- Xiaodian District Maternal and Child Health Care Hospital, Taiyuan 030032, PR China
| | - Jing He
- Department of Obstetrics and Gynecology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi 030032, PR China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China
| | - Huimin Wang
- Fengtai Mental Health Center, Beijing 100071, PR China
| | - Guangke Li
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China.
| | - Nan Sang
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
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Teyton A, Sun Y, Molitor J, Chen JC, Sacks D, Avila C, Chiu V, Slezak J, Getahun D, Wu J, Benmarhnia T. Examining the Relationship Between Extreme Temperature, Microclimate Indicators, and Gestational Diabetes Mellitus in Pregnant Women Living in Southern California. Environ Epidemiol 2023; 7:e252. [PMID: 37304340 PMCID: PMC10256373 DOI: 10.1097/ee9.0000000000000252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 04/26/2023] [Indexed: 06/13/2023] Open
Abstract
Few studies have assessed extreme temperatures' impact on gestational diabetes mellitus (GDM). We examined the relation between GDM risk with weekly exposure to extreme high and low temperatures during the first 24 weeks of gestation and assessed potential effect modification by microclimate indicators. Methods We utilized 2008-2018 data for pregnant women from Kaiser Permanente Southern California electronic health records. GDM screening occurred between 24 and 28 gestational weeks for most women using the Carpenter-Coustan criteria or the International Association of Diabetes and Pregnancy Study Groups criteria. Daily maximum, minimum, and mean temperature data were linked to participants' residential address. We utilized distributed lag models, which assessed the lag from the first to the corresponding week, with logistic regression models to examine the exposure-lag-response associations between the 12 weekly extreme temperature exposures and GDM risk. We used the relative risk due to interaction (RERI) to estimate the additive modification of microclimate indicators on the relation between extreme temperature and GDM risk. Results GDM risks increased with extreme low temperature during gestational weeks 20--24 and with extreme high temperature at weeks 11-16. Microclimate indicators modified the influence of extreme temperatures on GDM risk. For example, there were positive RERIs for high-temperature extremes and less greenness, and a negative RERI for low-temperature extremes and increased impervious surface percentage. Discussion Susceptibility windows to extreme temperatures during pregnancy were observed. Modifiable microclimate indicators were identified that may attenuate temperature exposures during these windows, which could in turn reduce the health burden from GDM.
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Affiliation(s)
- Anais Teyton
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California
- School of Public Health, San Diego State University, La Jolla, California
| | - Yi Sun
- Department of Environmental and Occupational Health, Program in Public Health, University of California, Irvine, California
| | - John Molitor
- College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon
| | - Jiu-Chiuan Chen
- Departments of Population & Public Health Sciences and Neurology, University of Southern California, Los Angeles, California
| | - David Sacks
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California
- Department of Obstetrics and Gynecology, University of Southern California, Keck School of Medicine, Los Angeles, California
| | - Chantal Avila
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California
| | - Vicki Chiu
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California
| | - Jeff Slezak
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California
| | - Darios Getahun
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California
- Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California
| | - Jun Wu
- Department of Environmental and Occupational Health, Program in Public Health, University of California, Irvine, California
| | - Tarik Benmarhnia
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California
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Khalil WJ, Akeblersane M, Khan AS, Moin ASM, Butler AE. Environmental Pollution and the Risk of Developing Metabolic Disorders: Obesity and Diabetes. Int J Mol Sci 2023; 24:8870. [PMID: 37240215 PMCID: PMC10219141 DOI: 10.3390/ijms24108870] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 04/25/2023] [Accepted: 05/13/2023] [Indexed: 05/28/2023] Open
Abstract
To meet the increased need for food and energy because of the economic shift brought about by the Industrial Revolution in the 19th century, there has been an increase in persistent organic pollutants (POPs), atmospheric emissions and metals in the environment. Several studies have reported a relationship between these pollutants and obesity, and diabetes (type 1, type 2 and gestational). All of the major pollutants are considered to be endocrine disruptors because of their interactions with various transcription factors, receptors and tissues that result in alterations of metabolic function. POPs impact adipogenesis, thereby increasing the prevalence of obesity in exposed individuals. Metals impact glucose regulation by disrupting pancreatic β-cells, causing hyperglycemia and impaired insulin signaling. Additionally, a positive association has been observed between the concentration of endocrine disrupting chemicals (EDCs) in the 12 weeks prior to conception and fasting glucose levels. Here, we evaluate what is currently known regarding the link between environmental pollutants and metabolic disorders. In addition, we indicate where further research is required to improve our understanding of the specific effects of pollutants on these metabolic disorders which would enable implementation of changes to enable their prevention.
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Affiliation(s)
- William Junior Khalil
- School of Medicine, Royal College of Surgeons in Ireland Bahrain, Busaiteen 15503, Bahrain
| | - Meriem Akeblersane
- School of Medicine, Royal College of Surgeons in Ireland Bahrain, Busaiteen 15503, Bahrain
| | - Ana Saad Khan
- School of Medicine, Royal College of Surgeons in Ireland Bahrain, Busaiteen 15503, Bahrain
| | - Abu Saleh Md Moin
- Research Department, Royal College of Surgeons in Ireland Bahrain, Busaiteen 15503, Bahrain
| | - Alexandra E. Butler
- Research Department, Royal College of Surgeons in Ireland Bahrain, Busaiteen 15503, Bahrain
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Liang W, Zhu H, Xu J, Zhao Z, Zhou L, Zhu Q, Cai J, Ji L. Ambient air pollution and gestational diabetes mellitus: An updated systematic review and meta-analysis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 255:114802. [PMID: 36934545 DOI: 10.1016/j.ecoenv.2023.114802] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/23/2023] [Accepted: 03/15/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVE We aimed to evaluate the relationship between the composition of particulate matter (PM) and gestational diabetes mellitus (GDM) by a comprehensively review of epidemiological studies. METHODS We systematically identified cohort studies related to air pollution and GDM risk before February 8, 2023 from six databases (PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and Chongqing VIP Chinese Science and Technology Periodical databases). We calculated the relative risk (RR) and its 95% confidence intervals (CIs) to assess the overall effect by using a random effects model. RESULTS This meta-analysis of 31 eligible cohort studies showed that exposure to PM2.5, PM10, SO2, and NO2 was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM2.5 found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO3-). Specifically, BC exposure in the second trimester and NO3- exposure in the first trimester elevated the risk of GDM, with the RR of 1.128 (1.032-1.231) and 1.128 (1.032-1.231), respectively. The stratified analysis showed stronger correlations of GDM risk with higher levels of pollutants in Asia, except for PM2.5 and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration. CONCLUSIONS Our study found that ambient air pollutant is a critical factor for GDM and further studies on specific particulate matter components should be considered in the future.
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Affiliation(s)
- Weiqi Liang
- Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China
| | - Hui Zhu
- Department of Internal Medicine, School of Medicine, Ningbo University, Ningbo, China
| | - Jin Xu
- Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China; Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, China
| | - Zhijia Zhao
- Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China
| | - Liming Zhou
- Center for Reproductive Medicine, Ningbo Women and Children's Hospital, Ningbo, China
| | - Qiong Zhu
- Department of Pediatrics, Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Jie Cai
- Center for Reproductive Medicine, Ningbo Women and Children's Hospital, Ningbo, China.
| | - Lindan Ji
- Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, China; Department of Biochemistry, School of Medicine, Ningbo University, Ningbo, China.
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23
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Yu S, Zhang M, Zhu J, Yang X, Bigambo FM, Snijders AM, Wang X, Hu W, Lv W, Xia Y. The effect of ambient ozone exposure on three types of diabetes: a meta-analysis. Environ Health 2023; 22:32. [PMID: 36998068 PMCID: PMC10061724 DOI: 10.1186/s12940-023-00981-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 03/13/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Ozone as an air pollutant is gradually becoming a threat to people's health. However, the effect of ozone exposure on risk of developing diabetes, a fast-growing global metabolic disease, remains controversial. OBJECTIVE To evaluate the impact of ambient ozone exposure on the incidence rate of type 1, type 2 and gestational diabetes mellitus. METHOD We systematically searched PubMed, Web of Science, and Cochrane Library databases before July 9, 2022, to determine relevant literature. Data were extracted after quality evaluation according to the Newcastle Ottawa Scale (NOS) and the agency for healthcare research and quality (AHRQ) standards, and a meta-analysis was used to evaluate the correlation between ozone exposure and type 1 diabetes mellitus (T1D), type 2 diabetes mellitus (T2D), and gestational diabetes mellitus (GDM). The heterogeneity test, sensitivity analysis, and publication bias were performed using Stata 16.0. RESULTS Our search identified 667 studies from three databases, 19 of which were included in our analysis after removing duplicate and ineligible studies. Among the remaining studies, three were on T1D, five were on T2D, and eleven were on GDM. The result showed that ozone exposure was positively correlated with T2D [effect size (ES) = 1.06, 95% CI: 1.02, 1.11] and GDM [pooled odds ratio (OR) = 1.01, 95% CI: 1.00, 1.03]. Subgroup analysis demonstrated that ozone exposure in the first trimester of pregnancy might raise the risk of GDM. However, no significant association was observed between ozone exposure and T1D. CONCLUSION Long-term exposure to ozone may increase the risk of T2D, and daily ozone exposure during pregnancy was a hazard factor for developing GDM. Decreasing ambient ozone pollution may reduce the burden of both diseases.
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Affiliation(s)
- Sirui Yu
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Institute of Toxicology, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Mingzhi Zhang
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Institute of Toxicology, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jiamin Zhu
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Institute of Toxicology, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China
| | - Xu Yang
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Institute of Toxicology, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Francis Manyori Bigambo
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Institute of Toxicology, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Antoine M Snijders
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Xu Wang
- Department of Endocrinology, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Weiyue Hu
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Institute of Toxicology, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China.
- Department of Nutrition and Food Safety, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China.
| | - Wei Lv
- Healthcare Management Program, School of Business, Nanjing University, 22 Hankou Rd, Nanjing, 210093, China.
| | - Yankai Xia
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Institute of Toxicology, School of Public Health, Nanjing Medical University, No.101 Longmian Road, Nanjing, 211166, China.
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
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Li C, Xu JJ, Zhou FY, Ge YZ, Qin KZ, Huang HF, Wu YT. Effects of Particulate Matter on the Risk of Gestational Hypertensive Disorders and Their Progression. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:4930-4939. [PMID: 36913485 PMCID: PMC10061918 DOI: 10.1021/acs.est.2c06573] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 02/16/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Associations between particulate matter (PM) and gestational hypertensive disorders (GHDs) are well documented, but there is no evidence on the associations between PM and GHD progression, especially among those with assisted reproductive technology (ART) conceptions. To explore the effects of PM on the risk of GHDs and their progression among pregnant women with natural or ART conception, we enrolled 185,140 pregnant women during 2014-2020 in Shanghai and estimated the associations during different periods using multivariate logistic regression. During the 3 months of preconception, 10 μg/m3 increases in PM concentrations were associated with increased risks of gestational hypertension (GH) (PM2.5: aOR = 1.076, 95% CI: 1.034-1.120; PM10: aOR = 1.042, 95% CI: 1.006-1.079) and preeclampsia (PM2.5: aOR = 1.064, 95% CI: 1.008-1.122; PM10: aOR = 1.048, 95% CI: 1.006-1.092 ) among women with natural conception. Furthermore, for women with ART conceptions who suffered current GHD, 10 μg/m3 increases in PM concentrations in the third trimester elevated the risk of progression (PM2.5: aOR = 1.156, 95% CI: 1.022-1.306 ; PM10: aOR = 1.134, 95% CI: 1.013-1.270). In summary, women with natural conception should avoid preconceptional PM exposure to protect themselves from GH and preeclampsia. For women with ART conceptions suffering from GHD, it is necessary to avoid PM exposure in late pregnancy to prevent the disease from progressing.
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Affiliation(s)
- Cheng Li
- Obstetrics
and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China
| | - Jing-Jing Xu
- Obstetrics
and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China
| | - Fang-Yue Zhou
- International
Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Ying-Zhou Ge
- Obstetrics
and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China
| | - Kai-Zhou Qin
- Obstetrics
and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China
| | - He-Feng Huang
- Obstetrics
and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China
- Research
Units of Embryo Original Diseases, Chinese
Academy of Medical Sciences, Shanghai 200011, China
- International
Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yan-Ting Wu
- Obstetrics
and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai 200011, China
- Research
Units of Embryo Original Diseases, Chinese
Academy of Medical Sciences, Shanghai 200011, China
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Nazarpour S, Ramezani Tehrani F, Valizadeh R, Amiri M. The relationship between air pollutants and gestational diabetes: an updated systematic review and meta-analysis. J Endocrinol Invest 2023:10.1007/s40618-023-02037-z. [PMID: 36807891 DOI: 10.1007/s40618-023-02037-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 02/08/2023] [Indexed: 02/21/2023]
Abstract
PURPOSE Air pollution is an environmental stimulus that may predispose pregnant women to gestational diabetes mellitus (GDM). This systematic review and meta-analysis were conducted to investigate the relationship between air pollutants and GDM. METHODS PubMed, Web of Science, and Scopus were systematically searched for retrieving English articles published from January 2020 to September 2021, investigating the relationship of exposure to ambient air pollution or levels of air pollutants with GDM and related parameters, including fasting plasma glucose (FPG), insulin resistance, and impaired glucose tolerance. Heterogeneity and publication bias were evaluated using I-squared (I2), and Begg's statistics, respectively. We also performed the subgroup analysis for particulate matters (PM2.5, PM10), Ozone (O3), and sulfur dioxide (SO2) in the different exposure periods. RESULTS A total of 13 studies examining 2,826,544 patients were included in this meta-analysis. Compared to non-exposed women, exposure to PM2.5 increases the odds (likelihood of occurrence outcome) of GDM by 1.09 times (95% CI 1.06, 1.12), whereas exposure to PM10 has more effect by OR of 1.17 (95% CI 1.04, 1.32). Exposure to O3 and SO2 increases the odds of GDM by 1.10 times (95% CI 1.03, 1.18) and 1.10 times (95% CI 1.01, 1.19), respectively. CONCLUSIONS The results of the study show a relationship between air pollutants PM2.5, PM10, O3, and SO2 and the risk of GDM. Although evidence from various studies can provide insights into the linkage between maternal exposure to air pollution and GDM, more well-designed longitudinal studies are recommended for precise interpretation of the association between GDM and air pollution by adjusting all potential confounders.
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Affiliation(s)
- S Nazarpour
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 24 Parvaneh, Yaman Street, Velenjak, P.O. Box: 19395-4763, Tehran, 1985717413, Islamic Republic of Iran
- Department of Midwifery, Varamin-Pishva Branch, Islamic Azad University, Tehran, Iran
| | - F Ramezani Tehrani
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 24 Parvaneh, Yaman Street, Velenjak, P.O. Box: 19395-4763, Tehran, 1985717413, Islamic Republic of Iran.
| | - R Valizadeh
- Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
- Minimally Invasive Surgery Research Center, Hazrat-e Rasool General Hospital, Iran University of Medical Sciences, Tehran, Iran.
| | - M Amiri
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 24 Parvaneh, Yaman Street, Velenjak, P.O. Box: 19395-4763, Tehran, 1985717413, Islamic Republic of Iran
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Xu R, Li Z, Qian N, Qian Y, Wang Z, Peng J, Zhu X, Guo C, Li X, Xu Q, Wei Y. Air pollution exposure and the risk of macrosomia: Identifying specific susceptible months. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 859:160203. [PMID: 36403833 DOI: 10.1016/j.scitotenv.2022.160203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/08/2022] [Accepted: 11/11/2022] [Indexed: 06/16/2023]
Abstract
Birth weight is an important indicator of future growth and development for newborns. Few studies investigated the potential effects of air pollutants on macrosomia and their susceptible windows. We included 38,971 singleton full-term births from Beijing HaiDian Maternal and Child Health Hospital between 2014 and 2018, and assessed the associations of air pollutants exposure during preconception and pregnancy with macrosomia as well as the corresponding susceptible windows. The concentrations of air pollutants (PM2.5, PM10, SO2, NO2, CO and O3) for participants were calculated by the data from the nearest monitoring stations. Distributed lag models (DLM) incorporating logistic regression models were used to estimate the associations between air pollutants exposure during the 3 months before conception and pregnancy period and the risk of macrosomia, identifying susceptible windows of air pollutants. Weighted quantile sum (WQS) regression was applied to estimate the joint effect of air pollutants. A 10 μg/m3 increase in PM2.5 exposure from 3rd to 8th gestational month was positively associated with the risk of macrosomia, with the strongest effect in the 6th month (OR = 1.010, 95 % CI: 1.002-1.019). For a 10 μg/m3 increase in SO2, the windows of significant exposure were from the 1st preconception month to the 3rd gestational month, with the strongest effect in the 2nd month (OR = 1.030, 95 % CI: 1.010-1.049). We also observed the significant positive associations were in the 5th-8th gestational months for PM10, the 8th-9th gestational months for NO2 and the 3rd-7th gestational months for CO respectively. WQS regression also indicated a positive association between co-exposure to air pollutants and macrosomia. Our results suggest air pollution exposure is associated with increased risk of macrosomia. The windows of exposure for susceptibility to the risk of macrosomia vary between air pollutants. The susceptible exposure windows were middle and late pregnancy for PM, CO and NO2, while for SO2, early pregnancy is the window of vulnerability. Our findings provide the evidence that air pollution exposure is an independent risk factor for macrosomia and a basis for targeted environment policy.
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Affiliation(s)
- Rongrong Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, China
| | - Zhigang Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Nianfeng Qian
- Hai Dian Maternal & Child Health Hospital, Beijing, China
| | - Yan Qian
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jianhao Peng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Xiaojing Zhu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Qiujin Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, China.
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Laine MK, Kautiainen H, Anttila P, Gissler M, Pennanen P, Eriksson JG. Early pregnancy particulate matter exposure, pre-pregnancy adiposity and risk of gestational diabetes mellitus in Finnish primiparous women: An observational cohort study. Prim Care Diabetes 2023; 17:79-84. [PMID: 36464621 DOI: 10.1016/j.pcd.2022.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 11/23/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022]
Abstract
AIMS To evaluate the association between the exposure of particulate matter with an aerodynamic diameter of ≤ 2.5μm (PM2.5) and with an aerodynamic diameter of ≤ 10μm (PM10) over the first trimester and the risk of gestational diabetes mellitus (GDM), and to assess whether maternal pre-pregnancy body mass index (BMI) modified the GDM risk. METHODS All Finnish primiparous women without previously diagnosed diabetes who delivered between 2009 and 2015 in the city of Vantaa, Finland, composed the study cohort (N = 6189). Diagnosis of GDM was based on a standard 75 g 2-hour oral glucose tolerance test. The average daily concentration of PM2.5 and PM10 over the first trimester was calculated individually for each woman. The relationship between exposure of PM2.5 and PM10 and GDM was analyzed with logistic models. RESULTS No association was observed between the average daily concentrations of PM2.5 and PM10 over the first trimester and the GDM risk. When simultaneously taking BMI and PM10 into account both mean daily PM10 concentration (p = 0.047) and pre-pregnancy BMI (p = 0.016) increased GDM risk independently and an interaction (p = 0.013) was observed between PM10 concentration and pre-pregnancy BMI. CONCLUSIONS Even globally low PM10 exposure level together with elevated maternal pre-pregnancy BMI seems to increase the GDM risk.
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Affiliation(s)
- Merja K Laine
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland.
| | - Hannu Kautiainen
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland; Primary Health Care Unit, Kuopio University Hospital, Kuopio, Finland.
| | - Pia Anttila
- Finnish Meteorological Institute, Helsinki, Finland.
| | - Mika Gissler
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland; Karolinska Institute, Stockholm, Sweden.
| | | | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland; National University Singapore, Yong Loo Lin School of Medicine, Department of Obstetrics and Gynecology, Singapore, Singapore; Singapore Institute for Clinical Sciences (SCIS), Agency for Science, Technology and Research (A⁎STAR), Singapore.
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28
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Zhang L, Wang P, Zhou Y, Cheng Y, Li J, Xiao X, Yin C, Li J, Meng X, Zhang Y. Associations of ozone exposure with gestational diabetes mellitus and glucose homeostasis: Evidence from a birth cohort in Shanghai, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159184. [PMID: 36202368 DOI: 10.1016/j.scitotenv.2022.159184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Associations between individual exposure to ozone (O3) and gestational diabetes mellitus (GDM) have rarely been investigated, and critical windows of O3 exposure for GDM have not been identified. OBJECTIVES We aimed to explore the associations of gestational O3 exposure with GDM and glucose homeostasis as well as to identify the potential critical windows. METHODS A total of 7834 pregnant women were included. Individual O3 exposure concentrations were evaluated using a high temporal-spatial resolution model. Each participant underwent an oral glucose tolerance test (OGTT) to screen for GDM between 24 and 28 gestational weeks. Multiple logistic and multiple linear regression models were used to estimate the associations of O3 with GDM risks and with blood glucose levels of OGTT, respectively. Distributed lag nonlinear models (DLNMs) were used to estimate the critical windows of O3 exposure for GDM. RESULTS Nearly 13.29 % of participants developed GDM. After controlling for covariates, we observed increased GDM risks per IQR increment of O3 exposure in the first trimester (OR = 1.738, 95 % CI: 1.002-3.016) and the first two trimesters (OR = 1.576, 95 % CI: 1.005-2.473). Gestational O3 exposure was positively associated with increased fasting blood glucose (the first trimester: β = 2.964, 95 % CI: 1.529-4.398; the first two trimesters: β = 1.620, 95 % CI: 0.436-2.804) and 2 h blood glucose (the first trimester: β = 6.569, 95 % CI: 1.775-11.363; the first two trimesters: β = 6.839, 95 % CI: 2.896-10.782). We also observed a concentration-response relationship of gestational O3 exposure with GDM risk, as well as fasting and 2 h blood glucose levels. Additionally, 5-10 gestational weeks was identified as a critical window of O3 exposure for GDM development. CONCLUSION In summary, we found that gestational O3 exposure disrupts glucose homeostasis and increases the risk of GDM in pregnant women. Furthermore, 5-10 gestational weeks could be a critical window for the effects of O3 exposure on GDM.
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Affiliation(s)
- Liyi Zhang
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Pengpeng Wang
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Yuhan Zhou
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Yukai Cheng
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Jialin Li
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Xirong Xiao
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
| | - Chuanmin Yin
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
| | - Jiufeng Li
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Xia Meng
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
| | - Yunhui Zhang
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
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Ren Z, Yuan J, Luo Y, Wang J, Li Y. Association of air pollution and fine particulate matter (PM2.5) exposure with gestational diabetes: a systematic review and meta-analysis. ANNALS OF TRANSLATIONAL MEDICINE 2023; 11:23. [PMID: 36760250 PMCID: PMC9906206 DOI: 10.21037/atm-22-6306] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 01/12/2023] [Indexed: 01/16/2023]
Abstract
Background The association between air pollution (AP) and gestational diabetes mellitus (GDM), especially between different pollutants and GDM, remains controversial and debatable. Hence, we conducted this systematic review and meta-analysis to provide comprehensive evidence-based support for the association between AP and GDM. Methods The databases of the Cochrane Library, Embase, PubMed, and Web of Science were searched from inception to 1 April 2022, in combination with manual retrieval. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of case-control studies and cohort studies, while the Joana Brigg's Institute (JBI) critical appraisal checklist was used for the quality assessment of cross-sectional studies. Results We identified 35 epidemiological studies (including 33 cohort studies, 1 cross-sectional study, and 1 case-control study) covering 6,939,725 pregnant women, of whom 865,460 were GDM patients. The NOS score of all included case-control studies and cohort studies was higher than six, and one of the included cross-sectional studies was rated as high quality according to the JBI assessment. Meta-analysis showed that fine particulate matter and air pollutants [PM2.5, odds ratio (OR) =1.06, 95% confidence interval (CI): 1.05-1.08, Z =7.76, P<0.001; PM10, OR =1.06, 95% CI: 1.01-1.11, Z =2.62, P=0.009; sulfur dioxide (SO2), OR =1.18, 95% CI: 1.10-1.26, Z = 4.69, P<0.001; nitric oxide (NO), OR =1.04, 95% CI: 1.03-1.06,Z =3.33, P=0.001; nitrogen oxides (NOX), OR =1.07, 95% CI: 1.04-1.11, Z =3.93, P<0.001; black carbon (BC), OR =1.08, 95% CI: 1.06-1.10, Z =7.58, P<0.001] was associated with GDM. Furthermore, no significant association was observed between O3, CO, and nitrogen dioxide (NO2) exposure and GDM. Conclusions Exposure to PM2.5, PM10, SO2, NO, NOX, and BC significantly increases the risk of GDM. AP is a remediable environmental trigger that can be prevented by human interventions, such as lowering AP levels or limiting human exposure to air pollutants. The government should strengthen the supervision of air quality and make air quality information more transparent. Besides, living conditions are crucial during pregnancy. Living in a place with more green areas is recommended, and indoor air purification should also be enhanced.
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Affiliation(s)
- Zhonglian Ren
- Department of Obstetrics and Gynecology, Chengdu Shuangliu District Maternal and Child Health Hospital, Chengdu, China
| | - Jiaying Yuan
- Science and education section, Chengdu Shuangliu District Maternal and Child Health Hospital, Chengdu, China
| | - Ya Luo
- Department of Obstetrics and Gynecology, Chengdu Shuangliu District Maternal and Child Health Hospital, Chengdu, China
| | - Juan Wang
- Department of Obstetrics and Gynecology, Chengdu Shuangliu District Maternal and Child Health Hospital, Chengdu, China
| | - Yanqin Li
- Department of Obstetrics and Gynecology, Chengdu Shuangliu District Maternal and Child Health Hospital, Chengdu, China
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Yang W, Johnson MB, Liao H, Liu Z, Zheng X, Lu C. Combined effect of preconceptional and prenatal exposure to air pollution and temperature on childhood pneumonia: A case-control study. ENVIRONMENTAL RESEARCH 2023; 216:114806. [PMID: 36375503 DOI: 10.1016/j.envres.2022.114806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 10/26/2022] [Accepted: 11/11/2022] [Indexed: 06/16/2023]
Abstract
Mounting evidence have linked ambient air pollution and temperature with childhood pneumonia, but it is unclear whether there is an interaction between air pollution and temperature on childhood pneumonia. We aim to assess the combined effect of ambient air pollution and temperature exposure during preconception and pregnancy on pneumonia by a case-control study of 1510 children aged 0-14 years in Changsha, China. We obtained the data of childhood pneumonia from XiangYa Hospital electrical records. We estimated personal exposure to outdoor air pollution (PM10, SO2 and NO2) by inverse distance weighted (IDW) method and temperature indicators. Multiple logistic regression models were used to evaluate associations of childhood pneumonia with air pollution, temperature (T), and diurnal temperature variation (DTV). We found that exposure to industry-related air pollution (PM10 and SO2) during preconception and pregnancy were associated with childhood pneumonia, with ORs (95% CI) of 1.72 (1.48-1.98) and 2.96 (2.50-3.51) during 1 year before pregnancy and 1.83 (1.59-2.11) and 3.43 (2.83-4.17) in pregnancy. Childhood pneumonia was negatively associated with T exposure during 1 year before pregnancy and pregnancy, with ORs (95% CI) of 0.57 (0.41-0.80) and 0.85 (0.74-0.98). DTV exposure during pregnancy especially during the 1st and 2nd trimesters significantly increased pneumonia risk, with ORS (95% CI) of 1.77 (1.19-2.64), 1.47 (1.18-1.83), and 1.37 (1.07-1.76) respectively. We further observed interactions of PM10 and SO2 exposure with low T and high DTV during conception and pregnancy in relation to childhood pneumonia. This study suggests that there were interactions air pollution with temperature and DTV on pneumonia development.
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Affiliation(s)
- Wenhui Yang
- XiangYa School of Public Health, Central South University, Changsha 410078, China
| | | | - Hongsen Liao
- XiangYa School of Public Health, Central South University, Changsha 410078, China
| | - Zijing Liu
- XiangYa School of Public Health, Central South University, Changsha 410078, China
| | - Xiangrong Zheng
- Department of Pediatrics, XiangYa Hospital, Central South University, Changsha, China
| | - Chan Lu
- XiangYa School of Public Health, Central South University, Changsha 410078, China.
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Liu W, Zhang Q, Liu W, Qiu C. Association between air pollution exposure and gestational diabetes mellitus in pregnant women: a retrospective cohort study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:2891-2903. [PMID: 35941503 DOI: 10.1007/s11356-022-22379-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/31/2022] [Indexed: 06/15/2023]
Abstract
The global prevalence of gestational diabetes mellitus (GDM) is increasing annually, and previous research reports on the relationship between exposure to air pollutants and GDM are not completely consistent. We investigated the association between air pollutant exposure and GDM in pregnant women in a retrospective cohort study in Guangzhou. We found that in the first trimester, exposure to PM2.5 and CO showed a significant association with GDM. In the second trimester, exposure to PM10 was significantly associated with GDM. In the third trimester, exposure to PM2.5, PM10, NO2, SO2, and CO at IQR4 (odds ratio [OR] = 1.271, 95% confidence interval [CI]: 1.179-1.370; OR = 1.283, 95% CI: 1.191-1.383; OR = 1.230, 95% CI: 1.145-1.322; OR = 1.408, 95% CI: 1.303-1.522; OR = 1.150, 95% CI: 1.067-1.240, respectively) compared with IQR1 was positively associated with GDM. However, exposure to NO2 was negatively associated with GDM in the first and second trimesters, and O3 was negatively associated with GDM in the second and third trimesters. We found that the correlation between air pollutants and GDM in different trimesters of pregnancy was not completely consistent in this retrospective cohort study. During pregnancy, there may be an interaction between air pollutant exposure and other factors, such as pregnant women's age, occupation, anemia status, pregnancy-induced hypertension status, and pregnancy season.
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Affiliation(s)
- Weiqi Liu
- Department of Clinical Laboratory, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, Guangdong, 510800, People's Republic of China.
| | - Qingui Zhang
- Department of Clinical Laboratory, Foshan Fosun Chancheng Hospital, Foshan, Guangdong, 528000, People's Republic of China
| | - Weiling Liu
- Department of Clinical Laboratory, Foshan Fosun Chancheng Hospital, Foshan, Guangdong, 528000, People's Republic of China
| | - Cuiqing Qiu
- Medical Information Office, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, Guangdong, 510800, People's Republic of China
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Zheng Y, Bian J, Hart J, Laden F, Soo-Tung Wen T, Zhao J, Qin H, Hu H. PM 2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2022; 291:119409. [PMID: 37151750 PMCID: PMC10162772 DOI: 10.1016/j.atmosenv.2022.119409] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Fine particulate matter (PM2.5) has been linked to gestational diabetes mellitus (GDM). However, PM2.5 is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24th gestation week) have distinct maternal characteristics and a higher risk of worse health outcomes compared with those with late-onset GDM (i.e., diagnosed in or after 24th gestation week). We aimed to examine differential impacts of PM2.5 and its constituents on early- vs. late-onset GDM, and to identify corresponding susceptible exposure windows. We leveraged statewide linked electronic health records and birth records data in Florida in 2012-2017. Exposures to PM2.5 and its constituents (i.e., sulfate [SO4 2-], ammonium [NH4 +], nitrate [NO3 -], organic matter [OM], black carbon [BC], mineral dust [DUST], and sea-salt [SS]) were spatiotemporally linked to pregnant women based on their residential histories. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of PM2.5 and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM2.5, SO4 2-, NH4 +, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM2.5 during weeks 1-12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM2.5 in the 1st and 2nd trimesters, SO4 2- in the 1st and 2nd trimesters, and NO3 - in the preconception and 1st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM2.5 and its constituents with early- vs. late-onset GDM, with different susceptible exposure windows. This study helps better understand the impacts of air pollution on GDM accounting for its physiological heterogeneity.
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Affiliation(s)
- Yi Zheng
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Jaime Hart
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Francine Laden
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Tony Soo-Tung Wen
- Department of Obstetrics and Gynecology, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Huaizhen Qin
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Hui Hu
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
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Li Z, Xu R, Wang Z, Qian N, Qian Y, Peng J, Zhu X, Guo C, Li X, Xu Q, Wei Y. Ozone exposure induced risk of gestational diabetes mellitus. CHEMOSPHERE 2022; 308:136241. [PMID: 36041521 DOI: 10.1016/j.chemosphere.2022.136241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/17/2022] [Accepted: 08/25/2022] [Indexed: 06/15/2023]
Abstract
Numerous studies have shown that air pollution seems to be able to cause many diseases. Considering the possible mechanism of action and the same growth trend, the present study is designed to examine whether and how air pollutants, especially ozone (O3) exposure, are associated with the incidence of gestational diabetes mellitus (GDM). By a retrospective cohort, we analyzed the records of 45439 pregnant women from 2013 to 2018 and matched them to maternal exposure to O3. We found that the increased odds of GDM is associated with increased O3 concentrations from the 1st month before pregnancy to the 3rd month during pregnancy. Specially, the odds ratios (ORs) of these associations were largest in the 1st month before pregnancy, suggesting that the effect of O3 pollution on GDM occurred in pre-pregnancy period. Moreover, the exposure-response plot in the 1st month before pregnancy showed that the odds of GDM increased with the increasing concentration of O3. Our findings provide the evidence that O3 exposure in both pre-pregnancy and pregnancy period elevates the odds of GDM, suggesting that more intensive air pollution controls are needed to improve the health of pregnant women and their offspring.
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Affiliation(s)
- Zhigang Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Rongrong Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, China
| | - Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Nianfeng Qian
- Hai Dian Maternal & Child Health Hospital, Beijing, China
| | - Yan Qian
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jianhao Peng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Xiaojing Zhu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Qiujin Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, China.
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Peterson AK, Habre R, Niu Z, Amin M, Yang T, Eckel SP, Farzan SF, Lurmann F, Pavlovic N, Grubbs BH, Walker D, Al-Marayati LA, Grant E, Lerner D, Bastain TM, Breton CV. Identifying pre-conception and pre-natal periods in which ambient air pollution exposure affects fetal growth in the predominately Hispanic MADRES cohort. Environ Health 2022; 21:115. [PMID: 36434705 PMCID: PMC9701016 DOI: 10.1186/s12940-022-00925-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/24/2022] [Indexed: 05/20/2023]
Abstract
BACKGROUND It is well documented that persons of color experience disproportionate exposure to environmental contaminants, including air pollution, and have poorer pregnancy outcomes. This study assessed the critical windows of exposure to ambient air pollution on in utero fetal growth among structurally marginalized populations in urban Los Angeles. METHODS Participants (N = 281) from the larger ongoing MADRES pregnancy cohort study were included in this analysis. Fetal growth outcomes were measured on average at 32 [Formula: see text] 2 weeks of gestation by a certified sonographer and included estimated fetal weight, abdominal circumference, head circumference, biparietal diameter and femur length. Daily ambient air pollutant concentrations were estimated for four pollutants (particulate matter less than 2.5 µm (PM2.5) and less than 10 µm (PM10) in aerodynamic diameter, nitrogen dioxide (NO2), and 8-h maximum ozone (O3)) at participant residences using inverse-distance squared spatial interpolation from ambient monitoring data. Weekly gestational averages were calculated from 12 weeks prior to conception to 32 weeks of gestation (44 total weeks), and their associations with growth outcomes were modeled using adjusted distributed lag models (DLMs). RESULTS Participants were on average 29 years [Formula: see text] 6 old and predominately Hispanic (82%). We identified a significant sensitive window of PM2.5 exposure (per IQR increase of 6 [Formula: see text]3) between gestational weeks 4-16 for lower estimated fetal weight [Formula: see text] averaged4-16 = -8.7 g; 95% CI -16.7, -0.8). Exposure to PM2.5 during gestational weeks 1-23 was also significantly associated with smaller fetal abdominal circumference ([Formula: see text] averaged1-23 = -0.6 mm; 95% CI -1.1, -0.2). Additionally, prenatal exposure to PM10 (per IQR increase of 13 [Formula: see text]3) between weeks 6-15 of pregnancy was significantly associated with smaller fetal abdominal circumference ([Formula: see text] averaged6-15 = -0.4 mm; 95% CI -0.8, -0.1). DISCUSSION These results suggest that exposure to particulate matter in early to mid-pregnancy, but not preconception or late pregnancy, may have critical implications on fetal growth.
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Affiliation(s)
- Alicia K Peterson
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Rima Habre
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Zhongzheng Niu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Monica Amin
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Tingyu Yang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Sandrah P Eckel
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Shohreh F Farzan
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Fred Lurmann
- Sonoma Technology Inc., Petaluma, CA, 94954, USA
| | | | - Brendan H Grubbs
- Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Daphne Walker
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Laila A Al-Marayati
- Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Edward Grant
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Deborah Lerner
- Eisner Health Medical Center, Los Angeles, CA, 90015, USA
| | - Theresa M Bastain
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA
| | - Carrie V Breton
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90032, USA.
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Starling AP, Wood C, Liu C, Kechris K, Yang IV, Friedman C, Thomas DSK, Peel JL, Adgate JL, Magzamen S, Martenies SE, Allshouse WB, Dabelea D. Ambient air pollution during pregnancy and DNA methylation in umbilical cord blood, with potential mediation of associations with infant adiposity: The Healthy Start study. ENVIRONMENTAL RESEARCH 2022; 214:113881. [PMID: 35835166 PMCID: PMC10402394 DOI: 10.1016/j.envres.2022.113881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 06/11/2022] [Accepted: 07/06/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Prenatal exposure to ambient air pollution has been associated with adverse offspring health outcomes. Childhood health effects of prenatal exposures may be mediated through changes to DNA methylation detectable at birth. METHODS Among 429 non-smoking women in a cohort study of mother-infant pairs in Colorado, USA, we estimated associations between prenatal exposure to ambient fine particulate matter (PM2.5) and ozone (O3), and epigenome-wide DNA methylation of umbilical cord blood cells at delivery (2010-2014). We calculated average PM2.5 and O3 in each trimester of pregnancy and the full pregnancy using inverse-distance-weighted interpolation. We fit linear regression models adjusted for potential confounders and cell proportions to estimate associations between air pollutants and methylation at each of 432,943 CpGs. Differentially methylated regions (DMRs) were identified using comb-p. Previously in this cohort, we reported positive associations between 3rd trimester O3 exposure and infant adiposity at 5 months of age. Here, we quantified the potential for mediation of that association by changes in DNA methylation in cord blood. RESULTS We identified several DMRs for each pollutant and period of pregnancy. The greatest number of significant DMRs were associated with third trimester PM2.5 (21 DMRs). No single CpGs were associated with air pollutants at a false discovery rate <0.05. We found that up to 8% of the effect of 3rd trimester O3 on 5-month adiposity may be mediated by locus-specific methylation changes, but mediation estimates were not statistically significant. CONCLUSIONS Differentially methylated regions in cord blood were identified in association with maternal exposure to PM2.5 and O3. Genes annotated to the significant sites played roles in cardiometabolic disease, immune function and inflammation, and neurologic disorders. We found limited evidence of mediation by DNA methylation of associations between third trimester O3 exposure and 5-month infant adiposity.
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Affiliation(s)
- Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Cheyret Wood
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Cuining Liu
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ivana V Yang
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA; Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Chloe Friedman
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Deborah S K Thomas
- Department of Geography and Earth Sciences, University of North Carolina Charlotte, NC, USA
| | - Jennifer L Peel
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
| | - John L Adgate
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Sheryl Magzamen
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA; Department of Epidemiology, Colorado School of Public Health, Colorado State University, Fort Collins, CO, USA
| | - Sheena E Martenies
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA; Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - William B Allshouse
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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Liu R, Zhang J, Chu L, Zhang J, Guo Y, Qiao L, Niu Z, Wang M, Farhat Z, Grippo A, Zhang Y, Ma C, Zhang Y, Zhu K, Mu L, Lei L. Association of ambient fine particulate matter exposure with gestational diabetes mellitus and blood glucose levels during pregnancy. ENVIRONMENTAL RESEARCH 2022; 214:114008. [PMID: 35931192 DOI: 10.1016/j.envres.2022.114008] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 07/12/2022] [Accepted: 07/26/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Previous studies have examined the associations between ambient fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM). However, limited studies explored the relationships between PM2.5 exposure and blood glucose levels during pregnancy, especially in highly polluted areas. OBJECTIVES To examine the associations of prenatal ambient PM2.5 exposure with GDM and blood glucose levels, and to identify the sensitive exposure windows in a highly air-polluted area. METHODS From July 2016 to October 2017, a birth cohort study was conducted in Beijing, China. Participants were interviewed in each trimester regarding demographics, lifestyle, living and working environment, and medical conditions. Participant's daily ambient PM2.5 levels from 3 m before last menstrual period (LMP) to the third trimester was estimated by a hybrid spatiotemporal model. Indoor air quality index was calculated based on environmental tobacco smoke, ventilation, cooking, painting, pesticide, and herbicide use. Distributed lag non-linear model was applied to explore the sensitive weeks of PM2.5 exposure. RESULTS Of 165 pregnant women, 23 (13.94%) developed GDM. After adjusting for potential confounders, PM2.5 exposure during the 1st trimester was associated with higher odds of GDM (10 μg/m3 increase: OR = 1.89, 95% CI: 1.04-3.49). Each 10 μg/m3 increase in PM2.5 during the 2nd trimester was associated with 17.70% (2.21-33.20), 15.99% (2.96-29.01), 18.82% (4.11-33.52), and 17.10% (3.28-30.92) increase in 1-h, 2-h, Δ1h-fasting (1-h minus fasting), and Δ2h-fasting (2-h minus fasting) blood glucose levels, respectively. PM2.5 exposure at 24th-27th weeks after LMP was associated with increased GDM risk. We identified sensitive exposure windows of 21st-24th weeks for higher 1-h and 2-h blood glucose levels and of 20th-22nd weeks for increased Δ1h-fasting and Δ2h-fasting. CONCLUSIONS Ambient PM2.5 exposure during the second trimester was associated with higher odds of GDM and higher blood glucose levels. Avoiding exposure to high air pollution levels during the sensitive windows might prevent women from developing GDM.
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Affiliation(s)
- Rujie Liu
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jun Zhang
- Research Center for Public Health, Tsinghua University, Beijing, China
| | - Li Chu
- Department of Obstetrics and Gynecology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Jun Zhang
- Department of Obstetrics and Gynecology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Yanjun Guo
- Department of Obstetrics and Gynecology, Aerospace Center Hospital, Beijing, China
| | - Lihua Qiao
- Research Center for Public Health, Tsinghua University, Beijing, China
| | - Zhongzheng Niu
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Zeinab Farhat
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Alexandra Grippo
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Yifan Zhang
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Changxing Ma
- Department of Biostatistics, School of Public Health and Health Professions, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Yingying Zhang
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Kexin Zhu
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Lina Mu
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, The State University of New York at Buffalo, Buffalo, NY, USA.
| | - Lijian Lei
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
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ÖZTÜRK DÖNMEZ R, KURT Ş. İklim Değişikliğinin Anne ve Yenidoğan Sağlığı Üzerine Etkisi. DOKUZ EYLÜL ÜNIVERSITESI HEMŞIRELIK FAKÜLTESI ELEKTRONIK DERGISI 2022. [DOI: 10.46483/deuhfed.1008043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Özellikle son yıllarda üzerinde durulan iklim değişikliği; on yıllardır süren sıcaklık, yağış, rüzgâr gibi hava olaylarındaki değişiklik olarak tanımlanmaktadır. İklim değişikliği ile birlikte, temiz suya erişim, hava kalitesi, hava sıcaklıklarında değişim, güvenli barınma ve gıda güvenliği gibi sağlığın belirleyicileri olumsuz etkilenerek insan sağlığı etkilenmektedir. Bu durumdan etkilenen risk grubunda bulunan bireyler, özellikle gebeler ve yenidoğanlar, savunmasız ve duyarlı alt grupları oluşturmaktadırlar. İklim değişikliği ve sağlığa etkilerini konu alan çalışmaların özellikle son yıllarda yürütülmüş olduğu dikkati çekmektedir. Bu derlemede iklim değişikliğinin anne ve yenidoğan sağlığı üzerine etkilerinin neler olduğuna dikkat çekilmek istenmiştir. İncelenen araştırmalardan yüksek derece sıcaklığa maruz kalma ve hava kirliliği ile gestasyonel diyabet, hipertansiyon, erken doğum, erken membran rüptürü, düşük doğum ağırlığı, ölü doğum, yenidoğan cinsiyeti ve konjenital anomaliler arasında ilişki olduğu saptanmıştır. İklim değişikliğinin sağlık üzerine olumsuz etkilerini azaltmada hemşirelere önemli sorumluluklar düşmektedir. Toplumun ve bireyin dayanıklılık kapasitesini arttırma, başa çıkma stratejilerini ve ileriye dönük davranışlarını geliştirme, sosyal destek ve yeşil çevre için politikalar geliştirmeye yönelik eğitici, savunucu, değişim ajanı, liderlik, bakım verici ve denetleyici gibi var olan rollerini hemşireler etkili bir biçimde kullanmalıdır.
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Affiliation(s)
| | - Şeyma KURT
- EGE ÜNİVERSİTESİ, SAĞLIK BİLİMLERİ ENSTİTÜSÜ
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Zhou X, Li C, Cheng H, Xie J, Li F, Wang L, Ding R. Association between ambient air pollution exposure during pregnancy and gestational diabetes mellitus: a meta-analysis of cohort studies. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:68615-68635. [PMID: 35543789 DOI: 10.1007/s11356-022-20594-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
Numerous studies have evaluated the association between air pollution and gestational diabetes mellitus (GDM), but the findings were inconsistent. This meta-analysis aimed to provide higher grade evidence on the association of air pollution with GDM based on previous studies. PubMed, Web of science, China National Knowledge Infrastructure (CNKI), and Wanfang Data Knowledge Service Platform (Wanfang) were searched comprehensively up to September 2021. Totally, 20 eligible cohort studies were finally included, for which the pooled RR and 95% CIs were estimated. Stratified analyses by study regions and units of pollutant increase were conducted for further investigation. Sensitivity analyses were also performed to assess the robustness. The finding showed that PM2.5, PM10, NO2, and SO2 exposure increased the risk of GDM, while O3 exposure reduced GDM risk. Specifically, PM2.5 exposure in the first and second trimesters, NO2 and SO2 exposure in the first trimester significantly increased the risk of GDM, with the RR ranging from 1.015 to 1.032. In addition, the elevation of GDM risk induced by PM2.5, PM10, and O3 exposure was more pronounced in Asian subjects than in American subjects. The meta-analysis provides high-quality evidence on the effect of maternal air pollution exposure on GDM in each exposure period.
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Affiliation(s)
- Xinyu Zhou
- First School of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Changlian Li
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Han Cheng
- First School of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Junyi Xie
- First School of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Feng Li
- First School of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Lishan Wang
- First School of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Rui Ding
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.
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Eberle C, Stichling S. Environmental health influences in pregnancy and risk of gestational diabetes mellitus: a systematic review. BMC Public Health 2022; 22:1572. [PMID: 35982427 PMCID: PMC9389831 DOI: 10.1186/s12889-022-13965-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 06/27/2022] [Indexed: 11/10/2022] Open
Abstract
Background Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications globally. Environmental risk factors may lead to increased glucose levels and GDM, which in turn may affect not only the health of the mother but assuming hypotheses of "fetal programming", also the health of the offspring. In addition to traditional GDM risk factors, the evidence is growing that environmental influences might affect the development of GDM. We conducted a systematic review analyzing the association between several environmental health risk factors in pregnancy, including climate factors, chemicals and metals, and GDM. Methods We performed a systematic literature search in Medline (PubMed), EMBASE, CINAHL, Cochrane Library and Web of Science Core Collection databases for research articles published until March 2021. Epidemiological human and animal model studies that examined GDM as an outcome and / or glycemic outcomes and at least one environmental risk factor for GDM were included. Results Of n = 91 studies, we classified n = 28 air pollution, n = 18 persistent organic pollutants (POP), n = 11 arsenic, n = 9 phthalate n = 8 bisphenol A (BPA), n = 8 seasonality, n = 6 cadmium and n = 5 ambient temperature studies. In total, we identified two animal model studies. Whilst we found clear evidence for an association between GDM and air pollution, ambient temperature, season, cadmium, arsenic, POPs and phthalates, the findings regarding phenols were rather inconsistent. There were clear associations between adverse glycemic outcomes and air pollution, ambient temperature, season, POPs, phenols, and phthalates. Findings regarding cadmium and arsenic were heterogeneous (n = 2 publications in each case). Conclusions Environmental risk factors are important to consider in the management and prevention of GDM. In view of mechanisms of fetal programming, the environmental risk factors investigated may impair the health of mother and offspring in the short and long term. Further research is needed. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-13965-5.
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Affiliation(s)
- Claudia Eberle
- Medicine With Specialization in Internal Medicine and General Medicine, Hochschule Fulda, University of Applied Sciences, Leipziger Strasse 123, 36037, Fulda, Germany.
| | - Stefanie Stichling
- Medicine With Specialization in Internal Medicine and General Medicine, Hochschule Fulda, University of Applied Sciences, Leipziger Strasse 123, 36037, Fulda, Germany
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40
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Cooper DB, Walker CJ, Christian WJ. Maternal proximity to mountain-top removal mining and birth defects in Appalachian Kentucky, 1997-2003. PLoS One 2022; 17:e0272998. [PMID: 35951600 PMCID: PMC9371306 DOI: 10.1371/journal.pone.0272998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 07/31/2022] [Indexed: 01/09/2023] Open
Abstract
Extraction of coal through mountaintop removal mining (MTR) alters many dimensions of the landscape. Explosive blasts, exposed rock, and coal washing have the potential to pollute air and water. Previous research suggests that infants born to mothers living in areas with MTR have a higher prevalence of birth defects. In this cross-sectional study, we further examine the relationship between MTR activity and several types of birth defects. Maternal exposure to MTR was assessed using remote sensing data from Skytruth, which captures MTR activity in the Central Appalachian region of the United States. Active MTR area was quantified within a five-kilometer buffer surrounding geocoded maternal address captured on birth records for live births to Appalachian Kentucky mothers between 1997 and 2003 (N = 95,581). We assigned high, medium, and low exposure based on the tertile of total MTR area within 5-km, and births with no MTR within this buffer were assigned zero exposure. The presence or absence of a birth defect grouped into six major organ systems was identified using birth records alone. Finally, we applied conditional multiple imputation for variables with missing values before conducting separate multivariable log-binomial regression models for each birth defect group. Prevalence ratio (PR) estimates were adjusted for individual level covariates from birth records. The prevalence of gastro-intestinal defects was significantly higher in birth records with high and low active MTR exposure compared to records with no exposure. (High exposure: PR = 1.99, 95% CI = 1.14-3.47; low exposure PR = 1.88, 95% CI = 1.06-3.31). This study supports some of the existing findings of previous ecological studies. Research addressing the relationship between gastro-intestinal birth defects and MTR coal mining is warranted but should carefully consider temporal dimensions of exposure.
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Affiliation(s)
- Daniel B. Cooper
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY, United States of America
| | - Courtney J. Walker
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY, United States of America
| | - W. Jay Christian
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY, United States of America
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41
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Tian Y, Fang J, Wang F, Luo Z, Zhao F, Zhang Y, Du P, Wang J, Li Y, Shi W, Liu Y, Ding E, Sun Q, Li C, Tang S, Yue X, Shi G, Wang B, Li T, Shen G, Shi X. Linking the Fasting Blood Glucose Level to Short-Term-Exposed Particulate Constituents and Pollution Sources: Results from a Multicenter Cross-Sectional Study in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:10172-10182. [PMID: 35770491 DOI: 10.1021/acs.est.1c08860] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Ambient PM2.5 (fine particulate matter with aerodynamic diameters ≤ 2.5 μm) is thought to be associated with the development of diabetes, but few studies traced the effects of PM2.5 components and pollution sources on the change in the fasting blood glucose (FBG). In the present study, we assessed the associations of PM2.5 constituents and their sources with the FBG in a general Chinese population aged over 40 years. Exposure to PM2.5 was positively associated with the FBG level, and each interquartile range (IQR) increase in a lag period of 30 days (18.4 μg/m3) showed the strongest association with an elevated FBG of 0.16 mmol/L (95% confidence interval: 0.04, 0.28). Among various constituents, increases in exposed elemental carbon, organic matter, arsenic, and heavy metals such as silver, cadmium, lead, and zinc were associated with higher FBG, whereas barium and chromium were associated with lower FBG levels. The elevated FBG level was closely associated with the PM2.5 from coal combustion, industrial sources, and vehicle emissions, while the association with secondary sources was statistically insignificant. Improving air quality by tracing back to the pollution sources would help to develop well-directed policies to protect human health.
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Affiliation(s)
- Yanlin Tian
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Feng Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Zhihan Luo
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yawei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Wanying Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yuanyuan Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Enmin Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qinghua Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Chengcheng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xu Yue
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Guoliang Shi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Bin Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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Song AY, Feinberg JI, Bakulski KM, Croen LA, Fallin MD, Newschaffer CJ, Hertz-Picciotto I, Schmidt RJ, Ladd-Acosta C, Volk HE. Prenatal Exposure to Ambient Air Pollution and Epigenetic Aging at Birth in Newborns. Front Genet 2022; 13:929416. [PMID: 35836579 PMCID: PMC9274082 DOI: 10.3389/fgene.2022.929416] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 05/23/2022] [Indexed: 11/24/2022] Open
Abstract
In utero air pollution exposure has been associated with adverse birth outcomes, yet effects of air pollutants on regulatory mechanisms in fetal growth and critical windows of vulnerability during pregnancy are not well understood. There is evidence that epigenetic alterations may contribute to these effects. DNA methylation (DNAm) based age estimators have been developed and studied extensively with health outcomes in recent years. Growing literature suggests environmental factors, such as air pollution and smoking, can influence epigenetic aging. However, little is known about the effect of prenatal air pollution exposure on epigenetic aging. In this study, we leveraged existing data on prenatal air pollution exposure and cord blood DNAm from 332 mother-child pairs in the Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk in Babies-Learning Early Signs (MARBLES), two pregnancy cohorts enrolling women who had a previous child diagnosed with autism spectrum disorder, to assess the relationship of prenatal exposure to air pollution and epigenetic aging at birth. DNAm age was computed using existing epigenetic clock algorithms for cord blood tissue-Knight and Bohlin. Epigenetic age acceleration was defined as the residual of regressing chronological gestational age on DNAm age, accounting for cell type proportions. Multivariable linear regression models and distributed lag models (DLMs), adjusting for child sex, maternal race/ethnicity, study sites, year of birth, maternal education, were completed. In the single-pollutant analysis, we observed exposure to PM2.5, PM10, and O3 during preconception period and pregnancy period were associated with decelerated epigenetic aging at birth. For example, pregnancy average PM10 exposure (per 10 unit increase) was associated with epigenetic age deceleration at birth (weeks) for both Knight and Bohlin clocks (β = -0.62, 95% CI: -1.17, -0.06; β = -0.32, 95% CI: -0.63, -0.01, respectively). Weekly DLMs revealed that increasing PM2.5 during the first trimester and second trimester were associated with decelerated epigenetic aging and that increasing PM10 during the preconception period was associated with decelerated epigenetic aging, using the Bohlin clock estimate. Prenatal ambient air pollution exposure, particularly in early and mid-pregnancy, was associated with decelerated epigenetic aging at birth.
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Affiliation(s)
- Ashley Y. Song
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Jason I. Feinberg
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Kelly M. Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Lisa A. Croen
- Division of Research, Kaiser Permanente, Oakland, CA, United States
| | - M. Daniele Fallin
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Craig J. Newschaffer
- College of Health and Human Development, Pennsylvania State University, State College, PA, United States
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, UC Davis, Davis CA and the UC Davis MIND Institute, Sacramento, CA, United States
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, UC Davis, Davis CA and the UC Davis MIND Institute, Sacramento, CA, United States
| | - Christine Ladd-Acosta
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Heather E. Volk
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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Cheng X, Ji X, Yang D, Zhang C, Chen L, Liu C, Meng X, Wang W, Li H, Kan H, Huang H. Associations of PM 2.5 exposure with blood glucose impairment in early pregnancy and gestational diabetes mellitus. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 232:113278. [PMID: 35131583 DOI: 10.1016/j.ecoenv.2022.113278] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/22/2022] [Accepted: 01/30/2022] [Indexed: 06/14/2023]
Abstract
Exposure to fine particulate matter (PM2.5) during pregnancy has been linked to the risk of gestational diabetes mellitus (GDM), while conclusions are inconsistent. In this study we aimed to estimate the effects of prenatal PM2.5 exposure with blood glucose in early pregnancy and the GDM risk. Participants were recruited from the SH-IPMCH-BTH cohort (n = 41,929), a study of air pollution and birth outcome. All participants provided serum samples for analyses of fasting blood glucose (FBG) and HbA1c during early pregnancy. GDM was diagnosed using an oral glucose tolerance test (OGTT) with the time interval of 1 h. Prenatal exposure to PM2.5 was estimated using gap-filled satellite exposure assessments in Shanghai, China. Both FBG and HbA1c levels were significantly and positively associated with PM2.5 exposure during early pregnancy. A 10 μg/m3 increase of PM2.5 exposure from early to middle pregnancy was associated with the risk of GDM (first trimester OR=1.09, 95% CI: 1.02, 1.16; second trimester OR=1.09, 95% CI: 1.03, 1.16; first two trimester OR=1.15, 95%CI: 1.04, 1.28). The combined effects were greater among elevated FBG and HbA1c women with higher PM2.5 exposure in middle trimester (P for interaction=0.037 and 0.001, respectively). This study found that exposure to PM2.5 exposure in the 1st and 2nd trimesters was related to GDM. FBG and HbA1c played roles in the relationship between PM2.5 exposure in the 2nd trimester and GDM.
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Affiliation(s)
- Xiaoyue Cheng
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China
| | - Xinhua Ji
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China
| | - Dongjian Yang
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China
| | - Chen Zhang
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Lei Chen
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Weidong Wang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Huichu Li
- Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University, Shanghai, China
| | - Hefeng Huang
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China.
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44
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Liu WY, Lu JH, He JR, Zhang LF, Wei DM, Wang CR, Xiao X, Xia HM, Qiu X. Combined effects of air pollutants on gestational diabetes mellitus: A prospective cohort study. ENVIRONMENTAL RESEARCH 2022; 204:112393. [PMID: 34798119 DOI: 10.1016/j.envres.2021.112393] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 10/19/2021] [Accepted: 11/13/2021] [Indexed: 06/13/2023]
Abstract
Exposures to multiple air pollutants during pregnancy have been associated with the risk of gestational diabetes mellitus (GDM). However, their combined effects are unclear. We aimed to evaluate the combined associations of five air pollutants from pre-pregnancy to the 2nd trimester with GDM. This study included 20,113 participants from the Born in Guangzhou Cohort Study (BIGCS). The inverse distance-weighted models were used to estimate individual air pollutant exposure, namely ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter less than 10 μm in diameter (PM10), and less than 2.5 μm in diameter (PM2.5). We estimated stage-specific associations of air pollutants with GDM using generalized estimating equation, and departures from additive joint effects were assessed using the relative excess risk (RERI) and the joint relative risk (JRR). Of the 20,113 participants, 3440 women (17.1%) were diagnosed with GDM. In the adjusted model, increased concentrations of O3 and SO2 3-6 months before pregnancy were associated with GDM occurrence, as well as O3 and PM10 in the 1st trimester, the adjusted relative risk (95% confident intervals) [RRs (95%CI)] ranged from 1.05 (1.00, 1.09) to 1.21 (1.04, 1.40). The largest JRR for GDM was the combination of SO2, NO2, and PM10 in the 1st trimester (JRR = 1.32, 95% CI: 1.10, 1.59). The JRR for O3 and SO2 was less than their additive joint effects [RERI = -0.25 (-0.47, -0.04), P for interaction = 0.048]. Associations of air pollutants with GDM differed somewhat by pre-pregnancy BMI and season. This study added new evidence to the current understanding of the combined effects of multiple air pollutants on GDM. Public health strategies were needed to reduce the adverse effects of air pollution exposure on pregnant women.
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Affiliation(s)
- Wen-Yu Liu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jin-Hua Lu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China; Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jian-Rong He
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China; Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Li-Fang Zhang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China; Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Dong-Mei Wei
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China; Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Cheng-Rui Wang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xiong Xiao
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Hui-Min Xia
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China; Provincial Clinical Research Center for Child Health, Guangdong, China
| | - Xiu Qiu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China; Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China; Provincial Clinical Research Center for Child Health, Guangdong, China.
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Mai D, Xu C, Lin W, Yue D, Fu S, Lin J, Yuan L, Zhao Y, Zhai Y, Mai H, Zeng X, Jiang T, Li X, Dai J, You B, Xiao Q, Wei Q, Hu Q. Association of abnormal-glucose tolerance during pregnancy with exposure to PM 2.5 components and sources. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118468. [PMID: 34748887 DOI: 10.1016/j.envpol.2021.118468] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 10/15/2021] [Accepted: 11/03/2021] [Indexed: 06/13/2023]
Abstract
Maternal exposure to PM2.5 has been associated with abnormal glucose tolerance during pregnancy, but little is known about which constituents and sources are most relevant to glycemic effects. We conducted a retrospective cohort study of 1148 pregnant women to investigate associations of PM2.5 chemical components with gestational diabetes mellitus (GDM) and impaired glucose tolerance (IGT) and to identify the most harmful sources in Heshan, China from January 2015 to July 2016. We measured PM2.5 using filter-based method and analyzed them for 28 constituents, including carbonaceous species, water-soluble ions and metal elements. Contributions of PM2.5 sources were assessed by positive matrix factorization (PMF). Logistic regression model was used to estimate composition-specific and source-specific effects on GDM/IGT. Random forest algorithm was applied to evaluate the relative importance of components to GDM and IGT. PM2.5 total mass and several chemical constituents were associated with GDM and IGT across the early to mid-gestation periods, as were the PM2.5 sources fossil fuel/oil combustion, road dust, metal smelting, construction dust, electronic waster, vehicular emissions and industrial emissions. The trimester-specific associations differed among pollutants and sources. The third and highest quartile of elemental carbon, ammonium (NH4+), iron (Fe) and manganese (Mn) across gestation were consistently associated with higher odds of GDM/IGT. Maternal exposures to zinc (Zn), titanium (Ti) and vehicular emissions during the first trimester, and vanadium (V), nickel (Ni), road dust and fossil fuel/oil combustion during the second trimester were more important for GDM/IGT. This study provides important new evidence that maternal exposure to PM2.5 components and sources is significantly related to elevated risk for abnormal glucose tolerance during pregnancy.
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Affiliation(s)
- Dejian Mai
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Chengfang Xu
- Department of Obstetrics and Gynecology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, Guangdong, China
| | - Weiwei Lin
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China.
| | - Dingli Yue
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou, 510308, China
| | - Shaojie Fu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Jianqing Lin
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Luan Yuan
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou, 510308, China
| | - Yan Zhao
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou, 510308, China
| | - Yuhong Zhai
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou, 510308, China
| | - Huiying Mai
- Department of Obstetrics and Gynecology, Heshan Maternal and Child Health Hospital, Heshan, 529700, Jiangmen, Guangdong, China
| | - Xiaoling Zeng
- Department of Obstetrics and Gynecology, Heshan Maternal and Child Health Hospital, Heshan, 529700, Jiangmen, Guangdong, China
| | - Tingwu Jiang
- Department of Clinical Laboratory, Heshan Maternal and Child Health Hospital, Heshan, 529700, Jiangmen, Guangdong, China
| | - Xuejiao Li
- Department of Obstetrics and Gynecology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, Guangdong, China
| | - Jiajia Dai
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Boning You
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Qin Xiao
- Experimental Teaching Center, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Qing Wei
- Experimental Teaching Center, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Qiansheng Hu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
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Sun Y, Li X, Benmarhnia T, Chen JC, Avila C, Sacks DA, Chiu V, Slezak J, Molitor J, Getahun D, Wu J. Exposure to air pollutant mixture and gestational diabetes mellitus in Southern California: Results from electronic health record data of a large pregnancy cohort. ENVIRONMENT INTERNATIONAL 2022; 158:106888. [PMID: 34563749 PMCID: PMC9022440 DOI: 10.1016/j.envint.2021.106888] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 09/07/2021] [Accepted: 09/17/2021] [Indexed: 05/14/2023]
Abstract
BACKGROUND Epidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents. OBJECTIVES To assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents. METHODS Detailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter < 2.5 μm (PM2.5), <10 μm (PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated using kriging interpolation of Environmental Protection Agency's routine monitoring station data, while PM2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon) were estimated using a fine-resolution geoscience-derived model. A multilevel logistic regression was used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of air pollution and PM component mixtures. Main analyses adjusted for maternal age, race/ethnicity, education, median family household income, pre-pregnancy BMI, smoking during pregnancy, insurance type, season of conception and year of delivery. RESULTS The incidence of GDM was 10.9% in the study population. In single-pollutant models, we observed an increased odds for GDM associated with exposures to PM2.5, PM10, NO2 and PM2.5 constituents. The association was strongest for NO2 [adjusted odds ratio (OR) per interquartile range: 1.176, 95% confidence interval (CI): 1.147-1.205)]. In multi-pollutant models, increased ORs for GDM in association with one quartile increase in air pollution mixtures were found for both kriging-based regional air pollutants (NO2, PM2.5, and PM10, OR = 1.095, 95% CI: 1.082-1.108) and PM2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon, OR = 1.258, 95% CI: 1.206-1.314); NO2 (78%) and black carbon (48%) contributed the most to the overall mixture effects among all krigged air pollutants and all PM2.5 constituents, respectively. The risk of GDM associated with air pollution exposure were significantly higher among Hispanic mothers, and overweight/obese mothers. CONCLUSION This study found that exposure to a mixture of ambient PM2.5, PM10, NO2, and PM2.5 chemical constituents was associated with an increased risk of GDM. NO2 and black carbon PM2.5 contributed most to GDM risk.
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Affiliation(s)
- Yi Sun
- Department of Environmental and Occupational Health, Program in Public Health, University of California, Irvine, CA, USA
| | - Xia Li
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Tarik Benmarhnia
- Herbert Wertheim School of Public Health and Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive #0725, CA La Jolla 92093, USA
| | - Jiu-Chiuan Chen
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Chantal Avila
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - David A Sacks
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA; Department of Obstetrics and Gynecology, University of Southern California, Keck School of Medicine, Los Angeles, CA, USA
| | - Vicki Chiu
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Jeff Slezak
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - John Molitor
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA
| | - Darios Getahun
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA.
| | - Jun Wu
- Department of Environmental and Occupational Health, Program in Public Health, University of California, Irvine, CA, USA.
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Yan YH, Chien CC, Wang P, Lu MC, Wei YC, Wang JS, Wang JS. Association of exposure to air pollutants with gestational diabetes mellitus in Chiayi City, Taiwan. Front Endocrinol (Lausanne) 2022; 13:1097270. [PMID: 36726471 PMCID: PMC9885121 DOI: 10.3389/fendo.2022.1097270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 12/30/2022] [Indexed: 01/17/2023] Open
Abstract
INTRODUCTION We investigated the associations of exposure to particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) and several gaseous pollutants with risk of gestational diabetes mellitus (GDM) in Taiwan. METHODS We retrospectively identified pregnant women who underwent a two-step approach to screen for GDM between 2006 and 2014. Information on concentrations of air pollutants (including PM2.5, sulfur dioxide [SO2], nitrogen oxides [NOx], and ozone [O3]) were collected from a single fixed-site monitoring station. We conducted logistic regression analyses to determine the associations between exposure to air pollutants and risk of GDM. RESULTS A total of 11210 women were analyzed, and 705 were diagnosed with GDM. Exposure to PM2.5 during the second trimester was associated with a nearly 50% higher risk of GDM (odds ratio [OR] 1.47, 95% CI 0.96 to 2.24, p=0.077). The associations were consistent in the two-pollutant model (PM2.5 + SO2 [OR 1.73, p=0.038], PM2.5 + NOx [OR 1.52, p=0.064], PM2.5 + O3 [OR 1.96, p=0.015]), and were more prominent in women with age <30 years and body mass index <25 kg/m2 (interaction p values <0.01). DISCUSSION Exposure to PM2.5 was associated with risk of GDM, especially in women who were younger or had a normal body mass index.
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Affiliation(s)
- Yuan-Horng Yan
- Department of Medical Research, Kuang Tien General Hospital, Taichung, Taiwan
- Department of Endocrinology and Metabolism, Kuang Tien General Hospital, Taichung, Taiwan
- Department of Nutrition and Institute of Biomedical Nutrition, Hung Kuang University, Taichung, Taiwan
| | - Chu-Chun Chien
- Department of Pathology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Pathology, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan
| | - Panchalli Wang
- Department of Obstetrics and Gynecology, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi, Taiwan
| | - Mei-Chun Lu
- Department of Medical Research, Kuang Tien General Hospital, Taichung, Taiwan
| | - Yu-Ching Wei
- Department of Pathology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Pathology, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan
| | - Jyh-Seng Wang
- Department of Pathology and Laboratory Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Jun-Sing Wang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- National Chung Hsing University, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
- *Correspondence: Jun-Sing Wang,
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Chen X, Zhao X, Jones MB, Harper A, de Seymour JV, Yang Y, Xia Y, Zhang T, Qi H, Gulliver J, Cannon RD, Saffery R, Zhang H, Han TL, Baker PN. The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester. Front Endocrinol (Lausanne) 2022; 13:1060309. [PMID: 36531491 PMCID: PMC9755849 DOI: 10.3389/fendo.2022.1060309] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 11/18/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort. METHODS A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites. RESULTS Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM2.5, PM10, SO2, NO2, CO and the exposure estimates of PM2.5 and NO2, and positively associated with O3. CONCLUSIONS This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.
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Affiliation(s)
- Xuyang Chen
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Xue Zhao
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Mary Beatrix Jones
- Department of Statistics, The University of Auckland, Auckland, New Zealand
| | - Alexander Harper
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | | | - Yang Yang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Yinyin Xia
- School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Ting Zhang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Stomatological Hospital of Chongqing Medical University, Chongqing, China
| | - Hongbo Qi
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - John Gulliver
- Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, United Kingdom
| | - Richard D. Cannon
- Department of Oral Sciences, Sir John Walsh Research Institute, Faculty of Dentistry, University of Otago, Dunedin, New Zealand
| | - Richard Saffery
- Molecular Immunity, Murdoch Children’s Research Institute, Royal Children’s Hospital, Melbourne, VIC, Australia
| | - Hua Zhang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- *Correspondence: Hua Zhang, ; Ting-Li Han,
| | - Ting-Li Han
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- Department of Obstetrics and Gynaecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Hua Zhang, ; Ting-Li Han,
| | - Philip N. Baker
- College of Life Sciences, University of Leicester, Leicester, United Kingdom
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Yu Y, Jerrett M, Paul KC, Su J, Shih IF, Wu J, Lee E, Inoue K, Haan M, Ritz B. Ozone Exposure, Outdoor Physical Activity, and Incident Type 2 Diabetes in the SALSA Cohort of Older Mexican Americans. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:97004. [PMID: 34494856 PMCID: PMC8425281 DOI: 10.1289/ehp8620] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 08/13/2021] [Accepted: 08/16/2021] [Indexed: 05/28/2023]
Abstract
BACKGROUND Type 2 diabetes is a leading contributor to the global burden of morbidity and mortality. Ozone (O3) exposure has previously been linked to diabetes. OBJECTIVE We studied the impact of O3 exposure on incident diabetes risk in elderly Mexican Americans and investigated whether outdoor physical activity modifies the association. METHODS We selected 1,090 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Ambient O3 exposure levels were modeled with a land-use regression built with saturation monitoring data collected at 49 sites across the Sacramento metropolitan area. Using Cox proportional hazard models, we estimated the risk of developing incident diabetes based on average O3 exposure modeled for 5-y prior to incident diabetes diagnosis or last follow-up. Further, we estimated outdoor leisure-time physical activity at baseline and investigated whether higher vs. lower levels modified the association between O3 exposure and diabetes. RESULTS In total, 186 incident diabetes cases were identified during 10-y follow-up. Higher levels of physical activity were negatively associated with incident diabetes [hazard ratio (HR)=0.64 (95% CI: 0.43, 0.95)]. The estimated HRs for incident diabetes was 1.13 (95% CI: 1.00, 1.28) per 10-ppb increment of 5-y average O3 exposure; also, this association was stronger among those physically active outdoors [HR=1.52 (95% CI: 1.21, 1.90)], and close to null for those reporting lower levels of outdoor activity [HR=1.04 (95% CI: 0.90, 1.20), pinteraction=0.01]. CONCLUSIONS Our findings suggest that ambient O3 exposure contributes to the development of type 2 diabetes, particularly among those with higher levels of leisure-time outdoor physical activity. Policies and strategies are needed to reduce O3 exposure to guarantee that the health benefits of physical activity are not diminished by higher levels of O3 pollution in susceptible populations such as older Hispanics. https://doi.org/10.1289/EHP8620.
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Affiliation(s)
- Yu Yu
- Department of Epidemiology, University of California at Los Angeles (UCLA) Fielding School of Public Health, Los Angeles, California, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Michael Jerrett
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Kimberly C. Paul
- Department of Epidemiology, University of California at Los Angeles (UCLA) Fielding School of Public Health, Los Angeles, California, USA
| | - Jason Su
- Division of Environmental Health Sciences, University of California, Berkley School of Public Health, Berkeley, California, USA
| | - I-Fan Shih
- Department of Epidemiology, University of California at Los Angeles (UCLA) Fielding School of Public Health, Los Angeles, California, USA
| | - Jun Wu
- Department of Environmental and Occupational Health, Program in Public Health, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Irvine, California, USA
| | - Eunice Lee
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, California, USA
| | - Kosuke Inoue
- Department of Epidemiology, University of California at Los Angeles (UCLA) Fielding School of Public Health, Los Angeles, California, USA
| | - Mary Haan
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, California, USA
| | - Beate Ritz
- Department of Epidemiology, University of California at Los Angeles (UCLA) Fielding School of Public Health, Los Angeles, California, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, California, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, California, USA
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50
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Takeda Y, Michikawa T, Morokuma S, Yamazaki S, Nakahara K, Yoshino A, Sugata S, Takami A, Saito S, Hoshi J, Kato K, Nitta H, Nishiwaki Y. Trimester-Specific Association of Maternal Exposure to Fine Particulate Matter and its Components With Birth and Placental Weight in Japan. J Occup Environ Med 2021; 63:771-778. [PMID: 34491964 DOI: 10.1097/jom.0000000000002254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE We investigated which trimester of exposure to PM2.5 and its components was associated with birth and placental weight, and the fetoplacental weight ratio. METHODS The study included 63,990 women who delivered singleton term births within 23 Tokyo wards between 2013 and 2015. Each day, we collected fine particles on a filter, and analyzed their chemical constituents, including carbons and ions. Trimester-specific exposure to each pollutant was estimated based on the average daily concentrations. RESULTS Over the third trimester, sulfate exposure tended to be inversely associated with birth weight, and decreased placental weight (difference for highest vs lowest quintile groups = -6.7 g, 95% confidence interval = -12.5 to -0.9). For fetoplacental weight ratio, there was no relationship. CONCLUSIONS Sulfate exposure over the third trimester may reduce birth weight, particularly placental weight.
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Affiliation(s)
- Yuki Takeda
- Department of Environmental and Occupational Health, Toho University Graduate School of Medicine, 5-21-16 Omori-nishi, Ota-ku, Tokyo 143-8540, Japan (Dr Takeda, Dr Michikawa, and Dr Nishiwaki); Department of Environmental and Occupational Health, School of Medicine, Toho University, 5-21-16 Omori-nishi, Ota-ku, Tokyo 143-8540, Japan (Dr Michikawa and Dr Nishiwaki); Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan (Dr Morokuma); Health and Environmental Risk Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan (Dr Yamazaki and Dr Nitta); Department of Obstetrics and Gynaecology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan (Dr Nakahara and Dr Kato); Regional Environment Conservation Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan (Dr Yoshino, Dr Sugata, and Dr Takami); Tokyo Metropolitan Research Institute for Environmental Protection, 1-7-5 Shinsuna, Koto-ku, Tokyo 136-0075, Japan (Dr Saito and Dr Hoshi)
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